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a vector of AIC values

logical. Should an explanation abouthow to read the output be printed? (default = TRUE).

a function

an environment in which to assign the parameters asvalues (default =.GlobalEnv)

a data object (a data frame or a data.table)

name of the variable that will be on the x axis of the barplot

name of the variable that will be on the y axis of the barplot

a vector of values, each of which represents an instance ofeither a "success" or "failure" (e.g., c("s", "f", "s", "s", "f", "s"))

which value(s) indicate "successes"?

(optional) which value(s) indicate "failures"?If no input is provided for this argument, then all the non-NA valuesthat are not declared to be "successes" will be treated as "failures".

hypothesized probability of success (default = 0.5)

indicates the alternative hypothesis and must beone of "two.sided", "greater", or "less". You can specify just theinitial letter. By default,alternative = "two.sided"

width of the confidence interval (default = 0.95)

number of decimal places to which to round thepercentages in the summary table (default = 0)

xmin

xmax

ymin

ymax

vertical

horizontal

open

bracket_shape

thickness

bracket_color

label

label_hjust

label_vjust

label_font_size

label_font_face

label_font_face

label_parse

a character string or a character vector

starting position of the susbtring (default = 1)

ending position of the susbtring (default = 1)

a data object (a data frame or a data.table)

a vector of old variable names(i.e., variable names to change)

a vector of new variable names

Ifskip_absent = TRUE, old variable namesthat do not exist in the data set will be skipped (default = TRUE).

Ifprint_summary = TRUE, a summary ofold and new variable names will printed. (default = TRUE)

type of the output. Ifoutput_type = "dt",the function's output will be a data.table with changed names.Ifoutput_type = "summary", the function's output willbe a data.table listing old and new variable names.By default,output_type = "dt".

R objects.

The function will test whether each input isof this mode. For example,check_modes(a, mode_to_confirm = "numeric"), the function will checkwhether the objecta is numeric.

a character vector containing names of packages to check

a data object (a data frame or a data.table)

name of the independent variable

name of the dependent variable (must be a binary variable)

number of decimal places to which toround the chi-squared test statistic (default = 2)

number of decimal places to which to round thep-value from the chi-squared test (default = 3)

number of significant digits to round to(for the table of proportions). By defaultsigfigs_proportion = 2

logical. Should continuity correction be applied?(default = TRUE)

width of the confidence interval for the odds ratio.Input can be any value less than 1 and greater than or equal to 0.By default,odds_ratio_ci = 0.95.Ifodds_ratio_ci = TRUE, the default value of 0.95 will be used.Ifodds_ratio_ci = FALSE, no confidence interval will be estimatedfor the odds ratio.

number of decimal places to which toround the limits of the odds ratio's confidence interval (default = 2)

logical. Whether the inverse of the odds ratio(i.e., 1 / odds ratio) should be returned.

ifTRUE, notify how many rowswere removed due to missing values. By default, NA count will be printedonly if there are any NA values.

ifsave_as_png = TRUE,the results will be saved as a PNG file (default = FALSE).

name of the PNG file to be saved. By default, the namewill be "chi_sq_" followed by a timestamp of thecurrent time.The timestamp will be in the format, jan_01_2021_1300_10_000001,where "jan_01_2021" would indicate January 01, 2021;1300 would indicate 13:00 (i.e., 1 PM); and 10_000001 wouldindicate 10.000001 seconds after the hour.

width of the PNG file (default = 1600)

height of the PNG file (default = 1200)

the units for thewidth andheight arguments.Can be"px" (pixels),"in" (inches),"cm",or"mm". By default,units = "px".

The nominal resolution in ppi which will be recordedin the png file, if a positive integer. Used for unitsother than the default. By default,res = 200

The layout argument for arranging sectiontitles and tables using thegrid.arrange function.

a data object (a data frame or a data.table)

name of the independent variable(must be a categorical variable)

name of the dependent variable (must be a binary variable)

focal value of the dependent variablewhose frequencies will be calculated (i.e., the value of thedependent variable that will be considered a "success" ora result of interest)

Ifcontingency_table = TRUE orifcontingency_table = "percentages", the percentage of eachbinary value within each group will be printed. Ifcontingency_table = "counts", a table of frequencies will beprinted. Ifcontingency_table = FALSE, no contingency tablewill be printed.

number of significant digits thatthe contingency table's percentage values should be rounded to(default = 2)

logical. Ifpercent_and_total = TRUE,tabulate percentages of the focal DV value and a total count ofthe two values in DV. By defaultpercent_and_total = FALSE

tabulate percentages of the focal DV value only

tabulate counts of the focal DV value only

number of significant digits to round to

ifchi_sq_test_stats = TRUE,chi-squared test statistic and degrees of freedom will be includedin the pairwise comparison data.table.

logical. Should continuity correction be applied?(default = TRUE)

ifsave_as_png = TRUE,the results will be saved as a PNG file (default = FALSE).

name of the PNG file to be saved. By default, the namewill be "chi_sq_" followed by a timestamp of thecurrent time.The timestamp will be in the format, jan_01_2021_1300_10_000001,where "jan_01_2021" would indicate January 01, 2021;1300 would indicate 13:00 (i.e., 1 PM); and 10_000001 wouldindicate 10.000001 seconds after the hour.

width of the PNG file (default = 2000)

height of the PNG file (default = 800)

the units for thewidth andheight arguments.Can be"px" (pixels),"in" (inches),"cm",or"mm". By default,units = "px".

The nominal resolution in ppi which will be recordedin the png file, if a positive integer. Used for unitsother than the default. By default,res = 200

The layout argument for arranging sectiontitles and tables using thegrid.arrange function.

a numeric vector

What is the desired confidence levelexpressed as a decimal? (default = 0.95)

ifTRUE, notify how many observationswere removed due to missing values. By default, NA count will be printedonly if there are any NA values.

a data object (a data frame or a data.table)

logical. Whether to remove datafrom survey preview (default = TRUE)

logical. Whether to remove datafrom test response (default = TRUE)

names of columns that Qualtricsincludes in the data set by default (e.g., "StartDate", "Finished").Accepting the default valuedefault_cols_by_qualtrics = NULLwill set the names to be those that Qualtrics uses as of Dec 25, 2020.

new names for columns thatQualtrics includes in the data set by default(e.g., "StartDate", "Finished").Accepting the default valuedefault_cols_by_qualtrics_new = NULLwill set the names to be those that Qualtrics uses as of Dec 25, 2020converted to snake_case (e.g., "start_date", "finished").

logical. whether to warn the user ifconverting character to numeric leads to loss of accuracy.(default = FALSE)

ifclick_data_cols = "rm",columns containing click data (e.g., "_First Click") will beremoved. Ifclick_data_cols = "move_to_right", the columnswill be moved to the right (end) of the data set.

ifpage_submit_cols = "rm",columns containing page submit data (e.g., "_Page Submit";"response time" data) will be removed.Ifpage_submit_cols = "move_to_right", the columnswill be moved to the right (end) of the data set.

a numeric vector

should coefficient of variation be calculated fora "population" or a "sample"?

a vector of values in the first of two samples

a vector of values in the second of two samples

a data object (a data frame or a data.table)

name of the independent variable

name of the dependent variable

range of the confidence interval for Cohen's d(default = 0.95)

Ifoutput_type == "all" orifoutput_type == "d_and_ci", the output willbe a vector of Cohen's d and its confidence interval.Ifoutput_type == "d", the output will be Cohen's d.Ifoutput_type == "ci", the output will be a vectorof the confidence interval around Cohen's d.By default,output_type == "all".

a vector of values in the first of two samples

a vector of values in the second of two samples

a data object (a data frame or a data.table)

name of the independent variable

name of the dependent variable

Ifdirection == "2_minus_1", Cohen's d willreflect the extent to which the mean of IV level 2 is greater thanthe mean of IV level 2. Ifdirection == "1_minus_2", Cohen's dwill reflect the extent to which the mean of IV level 1 is greater thanthe mean of IV level 2. By default,direction == "2_minus_1".

range of the confidence interval for Cohen's d(default = 0.95)

Ifoutput_type == "all" orifoutput_type == "d_var_se_and_ci", the output willbe a vector of Cohen's d and its variance, SE, and confidence interval.Ifoutput_type == "d_se_and_ci", the output willbe a vector of Cohen's d and its SE and confidence interval.Ifoutput_type == "d_and_ci", the output willbe a vector of Cohen's d and its confidence interval.Ifoutput_type == "d", the output will be Cohen's d.Ifoutput_type == "ci", the output will be a vectorof the confidence interval around Cohen's d.Ifoutput_type == "se", the output will be the standard errorof Cohen's d.By default,output_type == "all".

initial value of the noncentrality parameter foroptimization (default = 0). Adjust this value if confidenceinterval results look strange.

a numeric vector containing values whose mean will be calculated

the true mean

a vector of values in the first of two samples

a vector of values in the second of two samples

a data object (a data frame or a data.table)

name of the independent variable

name of the dependent variable

a data object (a data frame or a data.table)

name of the independent variable (grouping variable)

name of the dependent variable (measure variableof interest)

ifsave = TRUE, the plot will be savedas a PNG file.

name of the PNG file to be saved. By default, the namewill be "cohen_d_over_n_" followed by a timestamp of thecurrent time.The timestamp will be in the format, jan_01_2021_1300_10_000001,where "jan_01_2021" would indicate January 01, 2021;1300 would indicate 13:00 (i.e., 1 PM); and 10_000001 wouldindicate 10.000001 seconds after the hour.

title of the x-axis for the histogram by group.Ifxlab = FALSE, the title will be removed. By default(i.e., if no input is given),dv_name will be used asthe title.

title of the y-axis for the histogram by group.Ifylab = FALSE, the title will be removed. By default(i.e., if no input is given),iv_name will be used asthe title.

width of the plot to be saved. This argument will bedirectly entered as thewidth argument for theggsavefunction withinggplot2 package (default = 16)

height of the plot to be saved. This argument will bedirectly entered as theheight argument for theggsavefunction withinggplot2 package (default = 9)

Cohen's d (the input can be a vector of values)

sample size in the first of two group (the input can be avector of values)

sample size in the second of two group (the input can be avector of values)

(optional argument) variance of d(the input can be a vector of values). If this argument receives aninput, variance of r will be returned as well.

a vector of values in the first of two samples

a vector of values in the second of two samples

a data object (a data frame or a data.table)

name of the independent variable

name of the dependent variable

range of the confidence interval for Cohen's d(default = 0.95)

a data object (a data frame or a data.table)

a character vector containing names of columns, acrosswhich to combine data

a character string consisting of numbersseparated by commas

a data object (a data frame or a data.table)

another data object (a data frame or a data.table)

list of data objects (data.frame or data.table)

a data object (a data frame or a data.table)

name of the variable whose correlations with two othervariables will be compared.

name of the first of the two variables whosecorrelations withvar_1_name will be compared.

name of the second of the two variables whosecorrelations withvar_1_name will be compared.

logical. Should the p value based on a one-tailedt-test? (default = FALSE)

number of decimal places to which to roundcorrelation coefficients (default = 2)

number of decimal places to which to roundp-values (default = 3)

number of decimal places to which to round thet-statistic (default = 2)

logical. Should the summary be printed?(default = TRUE)

logical. Should the function return a summary tableas an output, as opposed to returning the output through the"invisible" function? (default = FALSE)

a vector of estimated effect sizes

a vector of variances of the effect sizes

logical. Should the statistics be rounded?(default = TRUE)

number of decimal places to which to roundp-values (default = 3)

number of decimal places to which to round thestandard errors of the difference (default = 2)

number of decimal places to which to round thez-statistic (default = 2)

logical. Should the p-values be roundedin a pretty format (i.e., lower threshold: "<.001").By default,pretty_round_p_value = TRUE.

a data object (a data frame or a data.table)

name of the independent variable (grouping variable)

name of the dependent variable (measure variableof interest)

number of significant digits to round to

statistics to calculate for each group.Ifstats = "basic",group size, mean, standard deviation, median, minimum, and maximum willbe calculated. Ifstats = "all", in addition to theaforementioned statistics, standard error, 95% confidence andprediction intervals, skewness, and kurtosis will also be calculated.Thestats argument can also be a character vector with types ofstatistics to calculate. For example, enteringstats = c("mean", "median") will calculate mean and median.By default,stats = "basic"

Should Welch's t-tests be conducted?By default,welch = TRUE

ifcohen_d = TRUE, Cohen's d statistics will beincluded in the pairwise comparison data.table.

ifcohen_d_w_ci = TRUE,Cohen's d with 95% CI will be included in the output data.table.

the name of the method to use to adjust p-values.Ifadjust_p = "holm", the Holm method will be used;ifadjust_p = "bonferroni", the Bonferroni method will be used.By default,adjust_p = "holm"

The use of this argument is deprecated.Use the 'adjust_p' argument instead.Ifbonferroni = TRUE, Bonferroni tests will beconducted for t-tests or Mann-Whitney tests.

ifTRUE, Mann-Whitney test results will beincluded in the pairwise comparison data.table.IfFALSE, Mann-Whitney tests will not be performed.

ift_test_stats = FALSE, t-test statisticand degrees of freedom will be excluded in the pairwise comparisondata.table. (default = TRUE)

number of decimal places to which to roundp-values (default = 3)

Should a one-way ANOVA be conducted and reported?By default,anova = FALSE, but when there are more than twolevels in the independent variable, the value will change such tatanova = TRUE.

number of decimal places to which to roundthe f statistic (default = 2)

number of decimal places to which to roundthe t statistic (default = 2)

number of decimal places to which to roundthe degrees of freedom for t tests (default = 2)

ifsave_as_png = "all" orifsave_as_png = TRUE,the histogram by group, descriptive statistics by group,and pairwise comparison results will be saved as a PNG file.

name of the PNG file to be saved. By default, the namewill be "compare_groups_results_" followed by a timestamp of thecurrent time.The timestamp will be in the format, jan_01_2021_1300_10_000001,where "jan_01_2021" would indicate January 01, 2021;1300 would indicate 13:00 (i.e., 1 PM); and 10_000001 wouldindicate 10.000001 seconds after the hour.

title of the x-axis for the histogram by group.Ifxlab = FALSE, the title will be removed. By default(i.e., if no input is given),dv_name will be used asthe title.

title of the y-axis for the histogram by group.Ifylab = FALSE, the title will be removed. By default(i.e., if no input is given),iv_name will be used asthe title.

a numeric vector with values of the endpointsof the x axis.

a numeric vector indicating the points at which toplace tick marks on the x axis.

a vector containing labels for the place tick markson the x axis.

width of the PNG file (default = 5000)

height of the PNG file (default = 3600)

the units for thewidth andheight arguments.Can be"px" (pixels),"in" (inches),"cm",or"mm". By default,units = "px".

The nominal resolution in ppi which will be recordedin the png file, if a positive integer. Used for unitsother than the default. By default,res = 300

The layout argument for arranging plots and tablesusing thegrid.arrange function.

ifcol_names_nicer = TRUE, column nameswill be converted from snake_case to an easier-to-eye format.

logical. Should the values in thedependent variable be converted to numeric for plotting thehistograms? (default = TRUE)

ifholm = TRUE, the relevant p values will beadjusted using Holm method (also known as the Holm-Bonferroni orBonferroni-Holm method)

correlation in the first sample

size of the first sample

correlation in the second sample

size of the first sample

logical. Should the p value based on a one-tailedt-test? (default = FALSE)

(only for displaying purposes) number of decimalplaces to which to round the p-value (default = 3)

(only for displaying purposes) number ofdecimal places to which to round the z-score (default = 2)

(only for displaying purposes) number ofdecimal places to which to round correlation coefficients (default = 2)

logical. Should the summary be printed?(default = TRUE)

type of the output. Ifoutput_type = "z",the function's output will be the z-score of the difference betweenthe two correlations. Ifoutput_type = "p", the function'soutput will be the p-value associated with the z-score of thedifference between the two correlations. By default,output_type = NULL, and the function will not return anyvalue other than the printed summary.

a data object (a data frame or a data.table)

name of the variable whose values will fill therows of the contingency table

name of the variable whose values will fill thecolumns of the contingency table

a vector whose values will fill the rows of thecontingency table

a vector whose values will fill the columns of thecontingency table

Ifoutput_type == "dt" the output will be acontingency table as a data.table object.Ifoutput_type == "table" the output will be a contingency tableas a table object.Ifoutput_type == "df" the output will be a contingencytable as a data.frame object.By default,output_type == "table".

a data object (a data frame or a data.table)

a character vector specifying classes of columnsthat will be converted. For example, ifclasses = "character",all columns of the class "character" will be converted–if they can beconverted. The current version of the function only supports convertingcharacter columns to numeric.

logical. whether to warn the user ifconverting character to numeric leads to loss of accuracy.(default = TRUE)

Ifprint_summary = TRUE, a summary ofconverted columns will printed. (default = TRUE)

Ifsilent = FALSE, a message regarding conversionfor a data.frame will be printed. Ifsilent = TRUE, this messagewill be suppressed. By default,silent = FALSE.

a character vector

a numeric vector of data values

a numeric vector of data values

(optional) a data object (a data frame or a data.table)

(optional) name of the first variable(if using a data set as an input)

(optional) name of the second variable(if using a data set as an input)

range of the confidence interval for the correlationcoefficient. Ifci_range = FALSE, no confidence intervalwill be estimated. By default,ci_range = 0.95.

number of decimal places to which to roundcorrelation coefficients (default = 2)

number of decimal places to which to roundp-values (default = 3)

type of the output. Ifoutput_type = "dt",the function's output will be a data.table with the results from thecorrelation analysis. Ifoutput_type = "summary", the function'soutput will be a statement (a string) summarizing the results fromthe correlation analysis. By default,output_type = "summary"

a data object (a data frame or a data.table)

names of the variables for which to calculateall pairwise correlations

names of the variables that will go on the rowsof the correlation matrix

names of the variables that will go on the columnsof the correlation matrix

number of decimal places to which to roundcorrelation coefficients (default = 2)

number of decimal places to which to roundp-values (default = 3)

which value should be filled in cells of thecorrelation matrix? Ifoutput_type = "r", correlationcoefficients; ifoutput_type = "p", p-values;ifoutput_type = "rp", correlation coefficients withsignificance symbols based on p-values;ifoutput_type = "n", sizes of the samples used to calculatethe correlation coefficients. By default,output_type = "rp"

logical. Ifnumbered_cols == TRUE andifidentical(row_var_names, col_var_names) == TRUE, thenthe columns will be numbered instead of containing variable names.

a numeric vector

ifoutput_type = "plot", return a cumulativepercentage plot; ifoutput_type = "dt", return a data.tablewith cumulative percentages. By default,output_type = "plot"

a numeric vector

ifoutput_type = "vector", return a vectorof descriptive statistics; ifoutput_type = "dt", return adata.table of descriptive statistics (default = "vector")

number of significant digits to round to (default = 3)

logical. Should the standard errors aroundthe mean be included in the descriptive stats?(default = FALSE)

logical. Should 95% CI be included in the descriptive stats?(default = FALSE)

logical. Should 95% PI be included in the descriptive stats?(default = FALSE)

logical. Should the skewness statistic be includedin the descriptive stats?(default = FALSE)

logical. Should the kurtosis statistic be includedin the descriptive stats?(default = FALSE)

ifTRUE, notify how many observationswere removed due to missing values. By default, NA count will be printedonly if there are any NA values.

ifTRUE, print the descriptive stats data.table

a data object (a data frame or a data.table)

name of the variable for which descriptivestatistics will be calculated

name(s) of grouping variables

statistics to calculate. Ifstats = "basic",group size, mean, standard deviation, median, minimum, and maximum willbe calculated. Ifstats = "all", in addition to theaforementioned statistics, standard error, 95% confidence andprediction intervals, skewness, and kurtosis will also be calculated.Thestats argument can also be a character vector with types ofstatistics to calculate. For example, enteringstats = c("mean", "median") will calculate mean and median.By default,stats = "all"

number of significant digits to round to

names of columns whose values will be rounded

a character vector of names of packages to keep attached

logical. Should a package be detached even though otherattached packages depend on it? By default,force = FALSE

logical. Ifkeep_kim = FALSE, Package 'kim'will be detached along with all other user-installed packages.Ifkeep_kim = TRUE, Package 'kim' will not be detached.By default,keep_kim = FALSE

a vector whose elements will be checked for duplicates

logical. Ifna.rm = TRUE, NA values in the vectorwill be removed before searching for duplicates.Ifna.rm = FALSE, NA values will be included in the searchas potentially duplicated values. By default,na.rm = TRUE.

number of significant digits to round to inthe percent column of the summary (default = 2)

type of output. Ifoutput = "summary", the function'soutput will be a data.table summarizing duplicated values andtheir counts. Ifoutput = "duplicated_values", the function'soutput will be a vector of duplicated values.Ifoutput = "non_duplicated_values", the function's output willbe a vector of non-duplicated values (default = "summary")

a character vector

the number of generations to go back (default = 1)

logical. Ifsilent = TRUE, a message will be printed.

message to print

a data object (a data frame or a data.table)

name of the dependent variable

name of the first independent variable

name of the second independent variable

restrict all analyses to observations havingthese values for the first independent variable

restrict all analyses to observations havingthese values for the second independent variable

number of significant digits to which to roundvalues in anova table (default = 3)

ifTRUE, conduct a robust ANOVA in addition.

number of bootstrap samples for robust ANOVA.The default is set at 2000, but consider increasing the numberof samples to 5000, 10000, or an even larger number, if slowerhandling time is not an issue.

ifTRUE, print a plot and enable returning an output(default = TRUE)

iferror_bar = "se"; error bars will be +/-1standard error; iferror_bar = "ci" error bars will be aconfidence interval

width of the confidence interval(default = 0.95 for 95 percent confidence interval).This argument will not apply whenerror_bar = "se"

graphically, width of the segmentsat the end of error bars (default = 0.13)

thickness of the error bars (default = 1)

should a caption be included to indicatethe width of the error bars? (default = TRUE).

colors of the lines connecting means (default = NULL)If the second IV has two levels, then by default,line_colors = c("red", "blue")

types of the lines connecting means (default = NULL)If the second IV has two levels, then by default,line_types = c("solid", "dashed")

thickness of the lines connecting group means,(default = 1)

size of the dots indicating group means (default = 3)

by how much should the group means and error barsbe horizontally offset from each other so as not to overlap?(default = 0.13)

a character string for the x-axis title. If noinput is entered, then, by default, the first value ofiv_name will be used as the x-axis title.

a character string for the y-axis title. If noinput is entered, then, by default,dv_name will be usedas the y-axis title.

position of the y axis title (default = 0.85).By default,y_axis_title_vjust = 0.85, which means that they axis title will be positioned at 85% of the way up from the bottomof the plot.

a character for the legend title. If no inputis entered, then, by default, the second value ofiv_namewill be used as the legend title. Iflegend_title = FALSE,then the legend title will be removed.

position of the legend:"none", "top", "right", "bottom", "left", "none"(default ="right")

output type can be one of the following:"anova_table","group_stats","plot","robust_anova_results","robust_anova_post_hoc_results","robust_anova_post_hoc_contrast","all"

name of the PNG file to be saved.Ifpng_name = TRUE, the name will be "factorial_anova_2_way_"followed by a timestamp of the current time.The timestamp will be in the format, jan_01_2021_1300_10_000001,where "jan_01_2021" would indicate January 01, 2021;1300 would indicate 13:00 (i.e., 1 PM); and 10_000001 wouldindicate 10.000001 seconds after the hour.

width of the PNG file (default = 7000)

height of the PNG file (default = 4000)

the units for thewidth andheight arguments.Can be"px" (pixels),"in" (inches),"cm",or"mm". By default,units = "px".

The nominal resolution in ppi which will be recordedin the png file, if a positive integer. Used for unitsother than the default. If not specified, taken as 300 ppito set the size of text and line widths.

The layout argument for arranging plots and tablesusing thegrid.arrange function.

a vector whose elements will be checked for duplicates

logical. Ifna.rm = TRUE, NA values in the vectorwill be removed before searching for duplicates.Ifna.rm = FALSE, NA values will be included in the searchas potentially duplicated values. By default,na.rm = TRUE.

number of significant digits to round to inthe percent column of the summary (default = 2)

type of output. Ifoutput = "summary", the function'soutput will be a data.table summarizing duplicated values andtheir counts. Ifoutput = "duplicated_values", the function'soutput will be a vector of duplicated values.Ifoutput = "non_duplicated_values", the function's output willbe a vector of non-duplicated values (default = "summary")

a (vector of) correlation coefficient(s)

a data object (a data frame or a data.table)

name of the binary independent variable

name of the dependent variable

name of the continuous moderator variable

name of the variables to control for

logical. Should the plot include ap-value for the interaction term?

order of levels in the independentvariable for legend. By default, it will be set as levels of theindependent variable ordered using R's base functionsort.

type of output (default = "reg_lines_plot").Possible inputs: "interactions_pkg_results", "simple_effects_plot","jn_points", "regions", "reg_lines_plot"

horizontally and vertically jitter dotsby a percentage of the respective ranges of x and y values.

horizontally jitter dots by a percentage of therange of x values

vertically jitter dots by a percentage of therange of y values

opacity of the dots (0 = completely transparent,1 = completely opaque). By default,dot_alpha = 0.5

size of the dots (default = 4)

font size for the interactionp value (default = 8)

logical. Should the labels forJohnson-Neyman point labels be added to the plot? (default = TRUE)

font size for Johnson-Neyman point labels(default = 8)

a vector of hjust values forJohnson-Neyman point labels. By default, the hjust value will be 0.5 forall the points.

logical. Should vertical lines bedrawn at the observed extreme values of the moderator if those valueslie in siginificant region(s)?(default = FALSE)

By how much should the label for theinteraction p-value be adjusted vertically?By default,interaction_p_vjust = -3)

margin for the plotBy defaultplot_margin = ggplot2::unit(c(75, 7, 7, 7), "pt")

position of the legend (default = "right").Iflegend_position = "none", the legend will be removed.

types of the regression lines for the two levelsof the independent variable.By default,reg_line_types = c("solid", "dashed")

types of the lines for Johnson-Neyman points.By default,jn_line_types = c("solid", "solid")

thickness of the lines at Johnson-Neyman points(default = 1.5)

colors for the two values of theindependent variable (default = c("red", "blue"))

color of the significant region, i.e., range(s)of the moderator variable for which simple effect of the independentvariable on the dependent variable is statistically significant.

opacity forsig_region_color.(0 = completely transparent, 1 = completely opaque).By default,sig_region_alpha = 0.08

color of the non-significant region,i.e., range(s) of the moderator variable for which simple effect ofthe independent variable on the dependent variable is notstatistically significant.

opacity fornonsig_region_color.(0 = completely transparent, 1 = completely opaque).By default,nonsig_region_alpha = 0.08

title of the x axis. By default, it will be setas input formod_name. Ifx_axis_title = FALSE, it willbe removed.

title of the y axis. By default, it will be setas input fordv_name. Ify_axis_title = FALSE, it willbe removed.

title of the legend. By default, it will be setas input foriv_name. Iflegend_title = FALSE, it willbe removed.

To how many digits after thedecimal point should the p value for the interaction term berounded? (default = 3)

thickness of the lines of fit (default = 1)

To how many digits after thedecimal point should the jn point labels be rounded? (default = 2)

a data object (a data frame or a data.table)

name of the binary independent variable

name of the binary dependent variable

name of the continuous moderator variable

logical. Should the plot include ap-value for the interaction term?

order of levels in the independentvariable for legend. By default, it will be set as levels of theindependent variable ordered using R's base functionsort.

order of levels in the dependent variable.By default, it will be set as levels of thedependent variable ordered using R's base functionsort.

the Minimum Distance inthe unit of the moderator variable that will be used for various purposes,such as (1) to disregard the second Johnson-Neyman pointthat is different from the first Johnson-Neyman (JN) point byless than the Minimum Distance; (2) to determine regions ofsignificance, which will calculate the p-value of the IV's effect(the focal dummy variable's effect) on DV at a candidateJN point + / - the Minimum Distance.This input is hard to explain, but a user can enter a really low valuefor this argument (e.g.,jn_points_disregard_threshold = 0.1for a moderator measured on a 100-point scale) or use the default.By default,jn_points_disregard_threshold = range of the moderator / 10000For example, if the observed moderator values range from 1 to 7(because it is a 7-point scale), thenjn_points_disregard_threshold = (7 - 1) / 10000 = 0.0006

type of output (default = "reg_lines_plot").Possible inputs: "interactions_pkg_results", "simple_effects_plot","jn_points", "regions", "reg_lines_plot"

How many spotlight analyses should beconducted to plot the predicted values at various values of themoderator? (default = 20)

horizontally jitter dots by a percentage of therange of x values (default = 0)

vertically jitter dots by a percentage of therange of y values (default = 5)

opacity of the dots (0 = completely transparent,1 = completely opaque). By default,dot_alpha = 0.3

size of the dots (default = 6)

font size for the interactionp value (default = 8)

logical. Should the labels forJohnson-Neyman point labels be added to the plot? (default = TRUE)

font size for Johnson-Neyman point labels(default = 8)

a vector of hjust values forJohnson-Neyman point labels. By default, the hjust value will be 0.5 forall the points.

By how much should the label for theinteraction p-value be adjusted vertically?By default,interaction_p_vjust = -3)

margin for the plotBy defaultplot_margin = ggplot2::unit(c(75, 7, 7, 7), "pt")

position of the legend (default = "right").Iflegend_position = "none", the legend will be removed.

types of the lines for plottingthe predicted valuesBy default,line_types_for_pred_values = c("solid", "dashed")

thickness of the linesfor plotting the predicted values (default = 2.5)

types of the lines for Johnson-Neyman points.By default,jn_line_types = c("solid", "solid")

thickness of the lines at Johnson-Neyman points(default = 1.5)

color of the significant region, i.e., range(s)of the moderator variable for which simple effect of the independentvariable on the dependent variable is statistically significant.

opacity forsig_region_color.(0 = completely transparent, 1 = completely opaque).By default,sig_region_alpha = 0.08

color of the non-significant region,i.e., range(s) of the moderator variable for which simple effect ofthe independent variable on the dependent variable is notstatistically significant.

opacity fornonsig_region_color.(0 = completely transparent, 1 = completely opaque).By default,nonsig_region_alpha = 0.08

title of the x axis. By default, it will be setas input formod_name. Ifx_axis_title = FALSE, it willbe removed.

title of the y axis. By default, it will be setas input fordv_name. Ify_axis_title = FALSE, it willbe removed.

title of the legend. By default, it will be setas input foriv_name. Iflegend_title = FALSE, it willbe removed.

To how many digits after thedecimal point should the p value for the interaction term berounded? (default = 3)

To how many digits after thedecimal point should the jn point labels be rounded? (default = 2)

a data object (a data frame or a data.table)

name of the binary independent variable

name of the binary dependent variable

name of the continuous moderator variable

logical. Should the plot include ap-value for the interaction term?

order of levels in the independentvariable for legend. By default, it will be set as levels of theindependent variable ordered using R's base functionsort.

order of levels in the dependent variable.By default, it will be set as levels of thedependent variable ordered using R's base functionsort.

the Minimum Distance inthe unit of the moderator variable that will be used for various purposes,such as (1) to disregard the second Johnson-Neyman pointthat is different from the first Johnson-Neyman (JN) point byless than the Minimum Distance; (2) to determine regions ofsignificance, which will calculate the p-value of the IV's effect(the focal dummy variable's effect) on DV at a candidateJN point + / - the Minimum Distance.This input is hard to explain, but a user can enter a really low valuefor this argument (e.g.,jn_points_disregard_threshold = 0.1for a moderator measured on a 100-point scale) or use the default.By default,jn_points_disregard_threshold = range of the moderator / 10000For example, if the observed moderator values range from 1 to 7(because it is a 7-point scale), thenjn_points_disregard_threshold = (7 - 1) / 10000 = 0.0006

type of output (default = "reg_lines_plot").Possible inputs: "interactions_pkg_results", "simple_effects_plot","jn_points", "regions", "reg_lines_plot"

How many spotlight analyses should beconducted to plot the predicted values at various values of themoderator? (default = 20)

horizontally jitter dots by a percentage of therange of x values (default = 0)

vertically jitter dots by a percentage of therange of y values (default = 5)

opacity of the dots (0 = completely transparent,1 = completely opaque). By default,dot_alpha = 0.3

size of the dots (default = 6)

font size for the interactionp value (default = 8)

font size for Johnson-Neyman point labels(default = 8)

a vector of hjust values forJohnson-Neyman point labels. By default, the hjust value will be 0.5 forall the points.

By how much should the label for theinteraction p-value be adjusted vertically?By default,interaction_p_vjust = -3)

margin for the plotBy defaultplot_margin = ggplot2::unit(c(75, 7, 7, 7), "pt")

position of the legend (default = "right").Iflegend_position = "none", the legend will be removed.

types of the lines for plottingthe predicted valuesBy default,line_types_for_pred_values = c("solid", "dashed")

thickness of the linesfor plotting the predicted values (default = 2.5)

types of the lines for Johnson-Neyman points.By default,jn_line_types = c("solid", "solid")

thickness of the lines at Johnson-Neyman points(default = 1.5)

color of the significant region, i.e., range(s)of the moderator variable for which simple effect of the independentvariable on the dependent variable is statistically significant.

opacity forsig_region_color.(0 = completely transparent, 1 = completely opaque).By default,sig_region_alpha = 0.08

color of the non-significant region,i.e., range(s) of the moderator variable for which simple effect ofthe independent variable on the dependent variable is notstatistically significant.

opacity fornonsig_region_color.(0 = completely transparent, 1 = completely opaque).By default,nonsig_region_alpha = 0.08

title of the x axis. By default, it will be setas input formod_name. Ifx_axis_title = FALSE, it willbe removed.

title of the y axis. By default, it will be setas input fordv_name. Ify_axis_title = FALSE, it willbe removed.

title of the legend. By default, it will be setas input foriv_name. Iflegend_title = FALSE, it willbe removed.

To how many digits after thedecimal point should the p value for the interaction term berounded? (default = 3)

To how many digits after thedecimal point should the jn point labels be rounded? (default = 2)

a data object (a data frame or a data.table)

name of the multicategorical independent variable;this variable must have three or more categories.

name of the dependent variable

name of the continuous moderator variable

names of the contrast variables

names of the contrast variables forwhich floodlight analyses will be conducted

name of the variables to control for

logical. Should the plot include ap-value for the interaction term?

order of levels in the independentvariable for legend. By default, it will be set as levels of theindependent variable ordered using R's base functionsort.

which kind ofheteroskedasticity-consistent (robust) standard errors should becalculated? (default = "HC4")

number of decimal places to which to roundr-squared values (default = 3)

number of decimal places to which to roundthe f statistic for model comparison (default = 2)

number of significant digits to round to(for values in the regression tables, except for p values).By defaultsigfigs = 2

the Minimum Distance inthe unit of the moderator variable that will be used for various purposes,such as (1) to disregard the second Johnson-Neyman pointthat is different from the first Johnson-Neyman (JN) point byless than the Minimum Distance; (2) to determine regions ofsignificance, which will calculate the p-value of the IV's effect(the focal dummy variable's effect) on DV at a candidateJN point + / - the Minimum Distance.This input is hard to explain, but a user can enter a really low valuefor this argument (e.g.,jn_points_disregard_threshold = 0.1for a moderator measured on a 100-point scale) or use the default.By default,jn_points_disregard_threshold = range of the moderator / 10000For example, if the observed moderator values range from 1 to 7(because it is a 7-point scale), thenjn_points_disregard_threshold = (7 - 1) / 10000 = 0.0006

Ifprint_floodlight_plots = TRUE,a floodlight plot for each dummy variable will be printed.By default,print_floodlight_plots = TRUE

output of the function (default = "all").Possible inputs: "reg_models", "reg_tables", "reg_tables_rounded","all"

horizontally jitter dots by a percentage of therange of x values

vertically jitter dots by a percentage of therange of y values

opacity of the dots (0 = completely transparent,1 = completely opaque). By default,dot_alpha = 0.5

size of the dots (default = 4)

font size for the interactionp value (default = 8)

font size for Johnson-Neyman point labels(default = 6)

a vector of hjust values forJohnson-Neyman point labels. By default, the hjust value will be 0.5 forall the points.

By how much should the label for theinteraction p-value be adjusted vertically?By default,interaction_p_vjust = -3)

margin for the plotBy defaultplot_margin = ggplot2::unit(c(75, 7, 7, 7), "pt")

position of the legend (default = "right").Iflegend_position = "none", the legend will be removed.

types of the lines of fit for the two levelsof the independent variable.By default,line_of_fit_types = c("solid", "dashed")

thickness of the lines of fit (default = 1.5)

types of the lines for Johnson-Neyman points.By default,jn_line_types = c("solid", "solid")

thickness of the lines at Johnson-Neyman points(default = 1.5)

color of the significant region, i.e., range(s)of the moderator variable for which simple effect of the independentvariable on the dependent variable is statistically significant.

opacity forsig_region_color.(0 = completely transparent, 1 = completely opaque).By default,sig_region_alpha = 0.08

color of the non-significant region,i.e., range(s) of the moderator variable for which simple effect ofthe independent variable on the dependent variable is notstatistically significant.

opacity fornonsig_region_color.(0 = completely transparent, 1 = completely opaque).By default,nonsig_region_alpha = 0.08

title of the x axis. By default, it will be setas input formod_name. Ifx_axis_title = FALSE, it willbe removed.

title of the y axis. By default, it will be setas input fordv_name. Ify_axis_title = FALSE, it willbe removed.

title of the legend. By default, it will be setas input foriv_name. Iflegend_title = FALSE, it willbe removed.

To how many digits after thedecimal point should the p value for the interaction term berounded? (default = 3)

To how many digits after thedecimal point should the jn point labels be rounded? (default = 2)

a data object (a data frame or a data.table)

name of the multicategorical independent variable;this variable must have three or more categories.

name of the dependent variable

name of the continuous moderator variable

name of the coding scheme to use; the current versionof the function allows only the "indicator" coding scheme.By default,coding = "indicator"

value of the independent variable thatwill be the reference value against which other values of theindependent variable will be compared

name of the variables to control for

logical. Should the plot include ap-value for the interaction term?

order of levels in the independentvariable for legend. By default, it will be set as levels of theindependent variable ordered using R's base functionsort.

which kind ofheteroskedasticity-consistent (robust) standard errors should becalculated? (default = "HC4")

number of decimal places to which to roundr-squared values (default = 3)

number of decimal places to which to roundthe f statistic for model comparison (default = 2)

number of significant digits to round to(for values in the regression tables, except for p values).By defaultsigfigs = 2

the Minimum Distance inthe unit of the moderator variable that will be used for various purposes,such as (1) to disregard the second Johnson-Neyman pointthat is different from the first Johnson-Neyman (JN) point byless than the Minimum Distance; (2) to determine regions ofsignificance, which will calculate the p-value of the IV's effect(the focal dummy variable's effect) on DV at a candidateJN point + / - the Minimum Distance.This input is hard to explain, but a user can enter a really low valuefor this argument (e.g.,jn_points_disregard_threshold = 0.1for a moderator measured on a 100-point scale) or use the default.By default,jn_points_disregard_threshold = range of the moderator / 10000For example, if the observed moderator values range from 1 to 7(because it is a 7-point scale), thenjn_points_disregard_threshold = (7 - 1) / 10000 = 0.0006

Ifprint_floodlight_plots = TRUE,a floodlight plot for each dummy variable will be printed.By default,print_floodlight_plots = TRUE

output of the function (default = "all").Possible inputs: "reg_models", "reg_tables", "reg_tables_rounded","all"

horizontally jitter dots by a percentage of therange of x values

vertically jitter dots by a percentage of therange of y values

opacity of the dots (0 = completely transparent,1 = completely opaque). By default,dot_alpha = 0.5

size of the dots (default = 4)

font size for the interactionp value (default = 8)

font size for Johnson-Neyman point labels(default = 8)

a vector of hjust values forJohnson-Neyman point labels. By default, the hjust value will be 0.5 forall the points.

By how much should the label for theinteraction p-value be adjusted vertically?By default,interaction_p_vjust = -3)

margin for the plotBy defaultplot_margin = ggplot2::unit(c(75, 7, 7, 7), "pt")

position of the legend (default = "right").Iflegend_position = "none", the legend will be removed.

types of the lines of fit for the two levelsof the independent variable.By default,line_of_fit_types = c("solid", "dashed")

thickness of the lines of fit (default = 1.5)

types of the lines for Johnson-Neyman points.By default,jn_line_types = c("solid", "solid")

thickness of the lines at Johnson-Neyman points(default = 1.5)

colors for the two values of theindependent variable (default = c("red", "blue"))

color of the significant region, i.e., range(s)of the moderator variable for which simple effect of the independentvariable on the dependent variable is statistically significant.

opacity forsig_region_color.(0 = completely transparent, 1 = completely opaque).By default,sig_region_alpha = 0.08

color of the non-significant region,i.e., range(s) of the moderator variable for which simple effect ofthe independent variable on the dependent variable is notstatistically significant.

opacity fornonsig_region_color.(0 = completely transparent, 1 = completely opaque).By default,nonsig_region_alpha = 0.08

title of the x axis. By default, it will be setas input formod_name. Ifx_axis_title = FALSE, it willbe removed.

title of the y axis. By default, it will be setas input fordv_name. Ify_axis_title = FALSE, it willbe removed.

title of the legend. By default, it will be setas input foriv_name. Iflegend_title = FALSE, it willbe removed.

To how many digits after thedecimal point should the p value for the interaction term berounded? (default = 3)

To how many digits after thedecimal point should the jn point labels be rounded? (default = 2)

default = NULL

default = NULL

default = NULL

default = c(2, 10)

default = 1

default = 0.3

default = NULL

default = NULL

default = NULL

default = NULL

default = 1.2

default = 0.3

default = -0.5

default = "black"

default = NULL

default = NULL

default = 6

default = 0

default = "bold"

default = 0

default = 6

default = "bold"

default = 2

default = "Observed Outcome"

default = 1

default = 0

default = "dotted"

default = 0

default = NULL

default = 60

default = 6

default = "plain"

default = NULL

default = 25

default = 0

default = 6

default = "plain"

default = NULL

default = 6

default = "none"

default = NULL

a numeric vector

the value to which zero or negativevalues will be converted to. Ifzero_or_neg_convert_to == NA,zero or negative values will be converted to NA values and thus beexcluded when calculating the geometric mean. (default = NA)

a character string of the png file name.By default, if no input is given (name = NULL),the file name will begin with "ggplot".If the desired output file name is "myplot.png",entername = "myplot", timestamp = FALSE

file name extension (default = "png").Iffile_name_extension = "svg", Package svglite needs tobe installed.

iftimestamp = TRUE, a timestamp of thecurrent time will be appended to the file name.The timestamp will be in the format, jan_01_2021_1300_10_000001,where "jan_01_2021" would indicate January 01, 2021;1300 would indicate 13:00 (i.e., 1 PM); and 10_000001 wouldindicate 10.000001 seconds after the hour.By default,timestamp will be set as TRUE, if no inputis given for thename argument, and as FALSE, if an inputis given for thename argument.

width of the plot to be saved. This argument will bedirectly entered as thewidth argument for theggsavefunction withinggplot2 package (default = 16)

height of the plot to be saved. This argument will bedirectly entered as theheight argument for theggsavefunction withinggplot2 package (default = 9)

a numeric vector

a numeric vector indicating breaks for the bins.By default, no input is required for this argument.

a numeric vector containing counts for the bins(i.e., heights of the bins). By default, no input is requiredfor this argument.

logical. Ifpercent = TRUE, percentageswill be plotted rather than frequencies (default = FALSE).

color of the area inside each bin(default = "green4")

color of the border around each bin(default = "black")

thickness of the border around each bin(default = 1)

ifTRUE, notify how many observationswere removed due to missing values. By default, NA count will be printedonly if there are any NA values.

a vector of values at which to place tick markson the x axis (e.g., settingx_axis_tick_marks = seq(0, 10, 5) willput tick marks at 0, 5, and 10.)

a vector of values at which to place tick markson the y axis (e.g., settingy_axis_tick_marks = seq(0, 10, 5) willput tick marks at 0, 5, and 10.)

logical. Should the axis lines be capped at theouter tick marks? (default = FALSE)

title for x axis (default = "Value")

title for y axis (default = "Count" or "Percentage",depending on the value ofpercent)

position of the y axis title (default = 0.85).

a data object (a data frame or a data.table)

name of the independent variable

name of the dependent variable

a character vector indicatingthe desired presentation order of levels in the independent variable(from the top to bottom). Omitting a group in this argument willremove the group in the set of histograms.

number of bins for the histograms (default = 40)

space between histograms(minimum = 0, maximum = 1, default = 0.15)

logical. Should the baseline and the trailinglines to either side of the histogram be drawn? (default = FALSE)

title of the x-axis for the histogram by group.Ifxlab = FALSE, the title will be removed. By default(i.e., if no input is given),dv_name will be used asthe title.

title of the y-axis for the histogram by group.Ifylab = FALSE, the title will be removed. By default(i.e., if no input is given),iv_name will be used asthe title.

a numeric vector with values of the endpointsof the x axis.

a numeric vector indicating the points at which toplace tick marks on the x axis.

a vector containing labels for the place tick markson the x axis.

number of significant digits to round to (default = 3)

logical. Should the values in thedependent variable be converted to numeric for plotting thehistograms? (default = TRUE)

a numeric vector

number of bins for the histogram (default = 30)

a vector of values at which to place tick markson the x axis (e.g., settingx_tick_marks = seq(0, 10, 5) willput tick marks at 0, 5, and 10.)

a vector of values at which to place tick markson the y axis (e.g., settingy_tick_marks = seq(0, 10, 5) willput tick marks at 0, 5, and 10.)

color for inside of the bins (default = "cyan4")

color for borders of the bins (default = "black")

position of the y axis title (default = 0.85).

title for x axis (default = "Value")

title for y axis (default = "Count")

logical. Should the axis lines be capped at theouter tick marks? (default = FALSE)

ifTRUE, notify how many observationswere removed due to missing values. By default, NA count will be printedonly if there are any NA values.

a numeric vector

a numeric vector indicating breaks for the bins.By default, no input is required for this argument.

a numeric vector containing counts for the bins(i.e., heights of the bins). By default, no input is requiredfor this argument.

logical. Ifpercent = TRUE, percentageswill be plotted rather than frequencies (default = FALSE).

color of the area inside each bin(default = "green4")

color of the border around each bin(default = "black")

thickness of the border around each bin(default = 1)

ifTRUE, notify how many observationswere removed due to missing values. By default, NA count will be printedonly if there are any NA values.

a vector of values at which to place tick markson the x axis (e.g., settingx_axis_tick_marks = seq(0, 10, 5) willput tick marks at 0, 5, and 10.)

a vector of values at which to place tick markson the y axis (e.g., settingy_axis_tick_marks = seq(0, 10, 5) willput tick marks at 0, 5, and 10.)

logical. Should the axis lines be capped at theouter tick marks? (default = FALSE)

title for x axis (default = "Value")

title for y axis (default = "Count" or "Percentage",depending on the value ofpercent)

position of the y axis title (default = 0.85).

a numeric vector

cutoff points for bins

logical. Should the leftmost bin treatedas an outlier bin? (default = TRUE)

logical. Should the rightmost bin treatedas an outlier bin? (default = TRUE)

a vector of values at which to place tick markson the x axis. Note that the first bar spans from 0.5 to 1.5,second bar from 1.5 to 2.5, ... nth bar from n - 0.5 to n + 0.5.See the example. By default, tick marks will be placed at everycutoff point for bins

a character vector to label tick marks.By default, the vector of cutoff points for bins will also beused as labels.

a vector of values at which to place tick markson the y axis (e.g., settingy_tick_marks = seq(0, 10, 5) willput tick marks at 0, 5, and 10.)

color to fill inside of theoutlier bins (default = "coral")

color to fill inside of thenon-outlier bins (default = "cyan4")

color for borders of the bins (default = "black")

position of the y axis title (default = 0.85).

title for x axis (default = "Value"). Ifx_axis_title = FALSE, x axis title will be removed from the plot.

title for y axis. By default, it will be either"Proportion" or "Count".

ifTRUE, notify how many observationswere removed due to missing values. By default, NA count will be printedonly if there are any NA values.

logical. Should proportions be plotted,as opposed to frequencies? (default = TRUE)

logical. Should frequencies be plotted,as opposed to proportions? (default = FALSE).Ifplot_frequency = TRUE,plot_proportion willswitch to be FALSE.

logical. Should mean marked on the histogram?(default = TRUE)

logical. Should 95% confidence interval marked on the histogram?(default = TRUE)

logical. Should median marked on the histogram?(default = TRUE)

position of the median label as a percentage ofheight of the tallest bin (default = 15)

size of the error bars (default = 3)

a numeric vector of p-values

a list of data.table objects

name of the column that will contain ID values.By default,id_col_name = "id".

position of the newly created ID column.Ifid_col_position = "first", the new ID column willbe placed as the first column in respective data sets.Ifid_col_position = "last", the new ID column willbe placed as the last column in respective data sets.

Ifsilent = TRUE, a summary of starting andending ID values in each data set will not be printed.Ifsilent = FALSE, a summary of starting andending ID values in each data set will be printed. (default = FALSE)

two or more R objects. If a vector or list is entered asan input, the function will test whether the vector's or list'selements are identical.

a numeric vector

logical. Ifunbiased = TRUE, the unbiasedestimate of the population kurtosis will be calculated.Ifunbiased = FALSE, the biased estimate of the populationkurtosis will be calculated. By default,unbiase = TRUE.

a vector or a data frame or an array or NULL.

a data object (a data frame or a data.table)

name of the dependent variable

name of the first independent variable

name of the second independent variable

number of decimal places to which to round theF-statistic from Levene's test (default = 2)

number of decimal places to which to round thep-value from Levene's test (default = 3)

Ifoutput_type = "text", the output will bethe results of Levene's test in a text format (i.e., character).Ifoutput_type = "list", the output will be the results ofLevene's test in a list format (e.g., p value, F stat, etc. as a list).By default,output_type = "text"

a data object (a data frame or a data.table)

name of the independent variable (grouping variable)

name of the dependent variable (binary outcome)

a contingency table, which can be directlyentered as an input for calculating the odds ratio

width of the confidence interval. Input can be any valueless than 1 and greater than or equal to 0. By default,ci = 0.95.Ifci = TRUE, the default value of 0.95 will be used. Ifci = FALSE, no confidence interval will be estimated.

logical. Should the output includevariance of the log of odds ratio? (default = FALSE)

logical. Whether the inverse of the odds ratio(i.e., 1 / odds ratio) should be returned.

log odds ratio (the input can be a vector of values),which will be converted to Cohen's d

logical. Should the names from the input be removed?(default = TRUE)

a data object (a data frame or a data.table)

name of the dependent variable (must be a binary variable)

name of the first independent variable

name of the second independent variable

number of decimal places to which to roundp-values (default = 3)

number of decimal places to which to roundchi square statistics (default = 2)

a vector with the ordered levels of thedependent variable, the first and second elements of which will becoded as 0 and 1, respectively, to run logistic regression.E.g.,dv_ordered_levels = c("fail", "pass")

(only if the first independent variableis a binary variable) a vector with the ordered levels of the firstindependent variable, the first and second elements of which will becoded as 0 and 1, respectively, to run logistic regression.E.g.,iv_1_ordered_levels = c("control", "treatment")

(only if the second independent variableis a binary variable) a vector with the ordered levels of the firstindependent variable, the first and second elements of which will becoded as 0 and 1, respectively, to run logistic regression.E.g.,iv_2_ordered_levels = c("male", "female")

logical. Should the output simply be aprintout of a one-line summary on the interaction term? (default = FALSE)

logical. Should the output simply be ap-value of the interaction term in the logistic regression model?(default = FALSE)

logical. Ifreturn_dt_w_binary = TRUE,the function will return a data.table with binary variables codedas 0 or 1 (default = FALSE)

a data object (a data frame or a data.table)

formula for estimating a single logistic regression model

formula for estimating logistic regression model 1 of 2

formula for estimating logistic regression model 2 of 2

logical. Should the z values be kept in the table?(default = FALSE)

logical. Should the row for the constantbe cleared except for b and standard error of b? (default = TRUE)

logical. Should the odds ratio columnsbe combined? (default = TRUE)

number of decimal places to which to roundb and standard error of b (default = 3)

number of decimal places to which to roundz values (default = 3)

number of decimal places to which to roundp-values (default = 3)

number of decimal places to which to roundodds ratios (default = 3)

number of decimal places to which to roundR-squared values (default = 3)

number of decimal places to which to roundmodel chi-squared values (default = 3)

logical. Should the p-values be roundedin a pretty format (i.e., lower threshold: "<.001").By default,pretty_round_p_value = TRUE.

logical. Should the default summaryoutput of the glm objects be printed? (default = FALSE)

logical. Should the summaries oflogistic regressions in a data table format be printed? (default = TRUE)

logical. Should the comparison oftwo logistic regression models be printed? (default = TRUE)

Ifoutput_type = "summary_dt_list" (default),the output of the function will be summaries of the two logisticregressions in a data.table format.Ifoutput_type = "glm_object_list", the output of thefunction will be the twoglm objects estimating logisticregression models. Ifoutput_type = "glm_default_summary_list",the output of the function will be the R's defaultsummaryoutput for the twoglm objects estimating logisticregression models. Ifoutput_type = "model_comparison_stats",the output of the function will be statistics from comparison of thetwo logistic regression models. Ifoutput_type = "all",the output of the function will be a list of the aforementioned outputs.

a glm object estimating alogistic regression model

logical. Should the z values be kept in the table?(default = FALSE)

logical. Should the row for the constantbe cleared except for b and standard error of b? (default = TRUE)

logical. Should the odds ratio columnsbe combined? (default = TRUE)

number of decimal places to which to roundb and standard error of b (default = 3)

number of decimal places to which to roundz values (default = 3)

number of decimal places to which to roundp-values (default = 3)

number of decimal places to which to roundodds ratios (default = 3)

number of decimal places to which to roundR-squared values (default = 3)

number of decimal places to which to roundmodel chi-squared values (default = 3)

logical. Should the p-values be roundedin a pretty format (i.e., lower threshold: "<.001").By default,pretty_round_p_value = TRUE.

a data object (a data frame or a data.table)

name of the dependent variable

name of the first independent variable

name of the second independent variable

restrict all analyses to observations havingthese values for the first independent variable

restrict all analyses to observations havingthese values for the second independent variable

type of the output. Ifoutput_type = "all",the function will return a results summary and print a mosaic plot.(default = "all")

number of decimal places to which to roundp-values (default = 3)

number of decimal places to which to roundchi-squared test statistics (default = 2)

Ifmosaic_plot = TRUE, a mosaic plot willbe printed (default = TRUE)

Ifreport_as_field = TRUE, reports summarywill follow the format suggested by Andy Field (2012)(ISBN: 978-1-4462-0045-2, p. 851)

a numeric vector

the threshold value for determining outliers.Ifthreshold == 2.5, the median plus or minus 2.5 times theMAD will be the cutoff values for determining outliers.In other words, values less than the median minus 2.5times the MAD and values greater than the median plus 2.5times the MAD will be considered outliers.By default,threshold == 2.5

scale factor for the 'mad' function in the 'stats'package. It is the constant linked to the assumed distribution.In case of normality, constant = 1.4826.By default,constant == 1.4826.

the value to which outliers will be converted.For example, ifconvert_outliers_to = NA, the outlier values willbe converted to NA values.Ifconvert_outliers_to = 1000, the outlier values willbe converted to 1000.By default,convert_outliers_to == NA.

type of the output.Ifoutput_type = "converted_vector",the function's output will be a vector with outliers converted tothe value set by the argumentconvert_outliers_to.Ifoutput_type = "outliers", the function's output will beoutliers in the original vector as determined by the MAD method.Ifoutput_type = "cutoff_values", the function'soutput will be the cutoff values for determining outliers.For example, if outliers will be values less than 0 and greater than 10,the cutoff values will be 0 and 10.Ifoutput_type = "non_outlier_values", the function's outputwill be a vector consisting only of the values that are not outliers;here, the outliers will be removed from the vector, rather thanbeing converted to NA values.By default,output_type = "converted_vector".

a data object (a data frame or a data.table)

name of the independent variable (grouping variable)

name of the dependent variable (measure variableof interest)

order of levels in the independentvariable. By default, it will be set as levels of theindependent variable ordered using R's base functionsort.

number of significant digits to round to

a vector of variable names, each of which will beheader of a row in the eventual matrix

a vector of variable names, each of which will beheader of a column in the eventual matrix

a numeric vector; though not thoroughly tested, the functioncan accept a matrix as an input.

a data object (a data frame or a data.table)

name of the independent variable

name of the mediator variable

name of the dependent variable

names of covariates to control for

ifTRUE, heteroskedasticity-consistentstandard errors will be used in quasi-Bayesian simulations. By default,it will be set asFALSE if nonparametric bootstrap is used andasTRUE if quasi-Bayesian approximation is used.

number of bootstrap samples. The default is set at 1000,but consider increasing the number of samples to 5000, 10000, or aneven larger number, if slower handling time is not an issue.

number of significant digits to round to

ifoutput_type = "summary_dt",return the summary data.table; ifoutput_type = "mediate_output",return the output from themediate function in the'mediate' package; ifoutput_type = "indirect_effect_p",return the p value associated with the indirect effect estimatedin the mediation model (default = "summary_dt")

ifsilent = FALSE, mediation analysis summary,estimation method, sample size, and number of simulations will beprinted; ifsilent = TRUE, nothing will be printed.(default = FALSE)

a list of data.table objects

name(s) of the column(s) that will contain the ID valuesin the two data tables. The name(s) of the ID column(s) must be identicalin the two data tables.

Ifsilent = TRUE, no message will be printedregarding how many ID values and column names were duplicated.Ifsilent = FALSE, messages will be printed regardinghow many column names were duplicated.In cases where only one column was used as the 'id' column (which is themost common case),silent = FALSE will also print messagesregarding how many input ID values were duplicated.By default,silent = FALSE.

the first data.table which will remain intact

the second data.table which will be joined outside of(around) the first data.table. If there are any duplicatedID values and column names across the two data tables, thecell values in the first data.table will remain intact andthe cell values in the second data.table will be discarded for theresulting merged data table.

name(s) of the column(s) that will contain the ID valuesin the two data tables. The name(s) of the ID column(s) must be identicalin the two data tables.

Ifsilent = TRUE, no message will be printedregarding how many ID values and column names were duplicated.Ifsilent = FALSE, messages will be printed regardinghow many column names were duplicated.In cases where only one column was used as the 'id' column (which is themost common case),silent = FALSE will also print messagesregarding how many input ID values were duplicated.By default,silent = FALSE.

a data object (a data frame or a data.table)

name of the between-group independent variable

names of the columns containingthe repeated measures

restrict all analyses toobservations having these values for the between-groupindependent variable

colors of the dots and lines connecting means(default = NULL) If there are exactly two repeated measures,then, by default,colors = c("red", "blue")

iferror_bar = "ci" error bars will be a 95%confidence interval; iferror_bar = "se", error bars will be +/-1standard error. By default,error_bar = "ci"

by how much should the group means and error barsbe horizontally offset from each other so as not to overlap?(default = 0.13)

a character for the legend title. If no inputis entered, then, by default, the legend title will be removed.

inputs for theadd parameterof theexpand argument. The first and second values respectivelydetermine the amount of space to add to the left and right alongthe x-axis. By default,x_axis_expansion_add = c(0.2, 0.03) whichmeans that space with the width of 0.2 will be added to the left, andspace with the width of 0.03 will be added to the right.

a character string for the x-axis title.Ifx_axis_title == FALSE, which is the default value,the x-axis title will be removed.

a character string for the y-axis title(default = "Mean"). Ifx_axis_title == FALSE, the y-axis titlewill be removed.

output type can be one of the following:"plot","all"

R objects.

a data object (a data frame or a data.table)

a formula object for the regression equation

(deprecated) a character vector specifying namesof variables that will be mean-centered before the regression modelis estimated

a character vector specifying namesof variables that will be mean-centered before the regression modelis estimated

number of significant digits to round to

round to nth digit after decimal(alternative tosigfigs)

number of decimal places to round p values(overrides all other rounding arguments)

logical. Should the p-values be roundedin a pretty format (i.e., lower threshold: "<.001").By default,pretty_round_p_value = TRUE.

logical. Should only the upper partof the table be returned?By default,return_table_upper_half = FALSE.

number of digits after the decimal both r-squaredand adjusted r-squared values should be rounded to (default 3)

number of digits after the decimal the f statisticof the regression model should be rounded to (default 2)

logical. Should the column namesof the regression table be made pretty (e.g., change "std_beta" to"Std. Beta")? (Default =TRUE)

Ifsilent = FALSE, a message regardingmean-centered variables will be printed. Ifsilent = TRUE,this message will be suppressed. By default,silent = FALSE.

ifsave_as_png = TRUE,the regression table will be saved as a PNG file (default = FALSE).

name of the PNG file to be saved. By default, the namewill be "mult_reg_" followed by a timestamp of thecurrent time.The timestamp will be in the format, jan_01_2021_1300_10_000001,where "jan_01_2021" would indicate January 01, 2021;1300 would indicate 13:00 (i.e., 1 PM); and 10_000001 wouldindicate 10.000001 seconds after the hour.

width of the PNG file (default = 1600)

height of the PNG file (default = 1200)

the units for thewidth andheight arguments.Can be"px" (pixels),"in" (inches),"cm",or"mm". By default,units = "px".

The nominal resolution in ppi which will be recordedin the png file, if a positive integer. Used for unitsother than the default. By default,res = 200

the t-statistic associated with the noncentrality parameters

degrees of freedom associated with the noncentrality parameters

initial value of the noncentrality parameter foroptimization (default = 0). Adjust this value if results look strange.

width of the confidence interval associated with thenoncentrality parameters (default = 0.95)

a data object (a data frame or a data.table)

name of the independent variable (grouping variable)

name of the dependent variable (binary outcome)

a contingency table, which can be directlyentered as an input for calculating the odds ratio

width of the confidence interval. Input can be any valueless than 1 and greater than or equal to 0. By default,ci = 0.95.Ifci = TRUE, the default value of 0.95 will be used. Ifci = FALSE, no confidence interval will be estimated.

number of decimal places to which toround the limits of the confidence interval (default = 2)

logical. Whether the inverse of the odds ratio(i.e., 1 / odds ratio) should be returned.

a data.table object

a character value indicatingthe name of the column by which to order the data.table

a vector indicating a specific order ofthe values in the column by which to order the data.table.

a numeric vector

a nonnegative constant by which interquartile range (IQR)will be multiplied to build a "fence," outside which observationswill be considered outliers. For example, ifiqr = 1.5,IQR * 1.5 will be the "fence" outside which observations will beconsidered to be outliers. By default,iqr = 1.5.

logical.na.rm argument to be passed onto the'quantile' function in the 'stats' package. If true, any NA and NaN'sare removed from x before the quantiles are computed.

type argument to be passed onto the 'quantile'function in the 'stats' package. An integer between 1 and 9 selectingone of the nine quantile algorithms detailed below to be used.Type '?stats::quantile' for details. By default,type = 7

logical. Ifunique_outliers = TRUE,the function will return the unique outlier values.Ifunique_outliers = FALSE, the function will return allthe outlier values in the vectorx.By default,unique_outliers = FALSE.

a number at which the first interval begins(the left INCLUSIVE endpoint of interval 1)

a number at which the first interval ends(the right INCLUSIVE endpoint of interval 1)

a number at which the second interval begins(the left INCLUSIVE endpoint of interval 2)

a number at which the second interval ends(the right INCLUSIVE endpoint of interval 2)

one or more R objects, to be converted to character vectors.This is the same argument that would be used in thepaste0 function.

an optional character string to separate the results.Not NA_character_.This is the same argument that would be used in thepaste0 function.

logical indicating if zero-length characterarguments should lead to the zero-length character(0)after the sep-phase (which turns into "" in thecollapse-phase, i.e., when collapse is not NULL).This is the same argument that would be used in thepaste0 function.

a vector of package types. By default,package_type = c("base", "recommended")

a data object (a data frame or a data.table)

names of the variables

number of random data sets. If no input is entered,this value will be set as 30 * number of variables.

percentile used in estimating bias(default = 95).

types of the lines connecting eigenvalues.By default,line_types = c("dashed", "solid")

size of the dots denoting eigenvalues (default = 5).

(optional) x coordinate ofthe label for eigenvalues from randomly generated data.

(optional) y coordinate ofthe label for eigenvalues from randomly generated data.

(optional) x coordinate ofthe label for unadjusted eigenvalues

(optional) y coordinate ofthe label for unadjusted eigenvalues

How much should labels for theeigenvalue curves be offset, as a percentage of the plot'sx and y range? (default = 2)

size of the labels for the eigenvalue curves(default = 6).

size of the dots denoting eigenvalues (default = 5).

thickness of the eigenvalue curves (default = 1.5).

position of the y axis title as aproportion of the range (default = 0.8).

size of the plot title (default = 26).

size of the text on the axes (default = 22).

a numeric vector

a data object (a data frame or a data.table)

names of variables for constructing rows

names of variables for constructing columnsindependent variables

function to perform for each cell inthe pivot table

number of significant digits to which to roundvalues in the pivot table (default = 3)

type of output. Ifoutput = "dt", the function'soutput will be a pivot table in a data.table format.Ifoutput = "subsets", the function's output will be a list ofdata tables that are subsets representing each cell in the pivot table.By default,output = "dt"

logical. Should the column names(i.e., v1, v2, ...) be removed in the data table output?

a data object (a data frame or a data.table)

name of the dependent variable

name(s) of the independent variable(s).Up to two independent variables can be supplied.

logical. Ifna.rm = TRUE, NA values inindependent and dependent variables will be removed beforecalculating group means.

iferror_bar = "se"; error bars will be +/-1standard error, iferror_bar = "ci" error bars will be aconfidence interval; iferror_bar = "pi", error bars will bea prediction interval

width of the confidence or prediction interval(default = 0.95 for 95 percent confidence or prediction interval).This argument will not apply whenerror_bar = "se"

graphically, width of the segmentsat the end of error bars (default = 0.13)

thickness of the error bars (default = 1)

should a caption be included to indicatethe width of the error bars? (default = TRUE).

logical. Should lines connecting meanswithin each group be drawn? (default = TRUE)

colors of the lines connecting means (default = NULL)If the second IV has two levels, then by default,line_colors = c("red", "blue")

types of the lines connecting means (default = NULL)If the second IV has two levels, then by default,line_types = c("solid", "dashed")

thickness of the lines connecting group means(default = 1)

Deprecated. Use the 'linewidth' argument instead.(default = 1)

size of the dots indicating group means (default = 3)

by how much should the group means and error barsbe horizontally offset from each other so as not to overlap?(default = 0.13)

a character string for the x-axis title. If noinput is entered, then, by default, the first value ofiv_name will be used as the x-axis title.

a character string for the y-axis title. If noinput is entered, then, by default,dv_name will be usedas the y-axis title.

position of the y axis title (default = 0.85).By default,y_axis_title_vjust = 0.85, which means that they axis title will be positioned at 85% of the way up from the bottomof the plot.

a character for the legend title. If no inputis entered, then, by default, the second value ofiv_namewill be used as the legend title. Iflegend_title = FALSE,then the legend title will be removed.

position of the legend:"none", "top", "right", "bottom", "left", "none"(default ="right")

one or more R objects, to be converted to character vectors.Input(s) to this argument will be passed onto the paste0 function.

an optional character string to separate the results.NotNA_character_. Input(s) to this argument will be passed ontothe paste0 function.

a numeric vector

ifTRUE, NA values will be removed before calculation

names of packages to load and attach, separated by commas,e.g.,"ggplot2", data.table. The input can be any numberof packages, whose names may or may not be wrapped in quotes.

logical. Ifpkg_names_as_object = TRUE,the input will be evaluated as one object containing package names.Ifpkg_names_as_object = FALSE, the input will be consideredas literal packages names (default = FALSE).

logical. Ifsilent_if_successful = TRUE,no message will be printed if preparation of package(s) is successful.Ifsilent_if_successful = FALSE, a message indicating whichpackage(s) were successfully loaded and attached will be printed(default = FALSE).

a character vector indicating names ofpackages to load silently (i.e., suppress messages that get printedwhen loading the packaged). By default,silent_load_pkgs = NULL

one number or a numeric vector

how many digits after the decimalpoint should the p-value be rounded to?

ifTRUE, output will be a string ofmathematical expression including "p", e.g., "p < .01" (default = FALSE)

a (vector of) correlation coefficient(s)

how many digits after the decimalpoint should the p-value be rounded to? (default = 2)

current number of iteration

iteration number at which the loop begins(default = 1)

iteration number at which the loop ends.

text to add before "Loop Progress..."By default, it is set to be blank, i.e.,text_before = ""

ifpercent = 1, progress level will be printedat every 1 percent progress (default = 1)

ifoutput_method = "cat", progress levelwill be printed using the 'cat' function;ifoutput_method = "return", progress level will bereturned as the output of the function (default = "cat")

a set of values that will count as successes (hits)

a numeric or character vector containingsuccesses (hits) and failures (misses)

ifTRUE, NA values will be removed both fromvector andvalues before calculation (default = TRUE).

By default,output_type = "proportion".Ifoutput_type = "proportion", the function will returnthe calculated proportion; ifoutput_type = "se", the functionwill return the standard error of the sample proportion;ifoutput_type = "dt", the function will return thethe data table of proportion and confidence intervals.

Ifsilent = TRUE, no message will be printedregarding number of NA values or confidence interval. (default = FALSE)

confidence level of the returned confidence interval.Input to this argument will be passed onto the conf.level argumentin theprop.test function from the default stats package.

a logical indicating whether Yates' continuitycorrection should be applied where possible (default = TRUE).Input to this argument will be passed onto thecorrect argumentin theprop.test function from the default stats package.

a vector of z values

a vector of sample sizes which will be used to calculate theweights, which in turn will be used to calculate the weighted z.

a character string of the csv file name without the".csv" extension. For example, if the csv file to read is "myfile.csv",entername = "myfile"

logical. ifhead = TRUE, prints the first fiverows of the data set.

a character string of the directory containingthe csv file, e.g.,dirname = "c:/Users/Documents"

optional arguments for thefread functionfrom the data.table package. Any arguments for data.table'sfreadfunction can be used, e.g.,fill = TRUE,nrows = 100

logical. ifhead = TRUE, prints the first fiverows of the data set.

optional arguments for thefread functionfrom the data.table package. Any arguments for data.table'sfreadfunction can be used, e.g.,fill = TRUE,nrows = 100

a regular expressionprovided, a default theme will be used.

a character vector in which to search for regularexpression matches, or a data table whose column names will be searched

logical. Ifsilent = FALSE, a report on regularexpression matches will be printed. Ifsilent = TRUE, the reporton regular expression matches will not be printed.By default,silent = FALSE

logical. Should Perl-compatible regexps be used?

a value whose relative position is to be searched in a vector

a numeric vector

a numeric vector

position of a vector

a single value or a vector of values which will beremoved from the target vector

a character or numeric vector

ifsilent = FALSE, a summary of values removedwill be printed; ifsilent = TRUE, such summary will not beprinted. By default,silent = FALSE

a character vector of names of packages to keep

a character vector indicating typesof packages to keep. The default,type_of_pkg_to_keep = c("base", "recommended"), keeps allbase and recommended packages that come with R when R is installed.

logical. Ifkeep_kim = FALSE, Package 'kim'will be removed along with all other user-installed packages.Ifkeep_kim = TRUE, Package 'kim' will not be removed.By default,keep_kim = FALSE

a data object (a data frame or a data.table)

name of the column identifying participants

names of the columns containing repeated measures(within-subjects variables)

logical. Ifhistograms = TRUE, histogramsof the repeated measures will be plotted. Ifhistograms = FALSE,no histograms will be plotted.

number of decimal places to which to roundW statistic from Mauchly's test (default = 2)

number of decimal places to which to roundthe epsilon statistic from Greenhouse-Geisser or Huynh-Feldtcorrection (default = 2)

number of decimal places to which to roundthe corrected degrees of freedom for model (default = 2)

number of decimal places to which to roundthe corrected degrees of freedom for error (default = 2)

number of decimal places to which to roundthe F statistic (default = 2)

number of decimal places to which to roundgeneralized eta-squared (default = 2)

a data object (a data frame or a data.table)

a vector of old values that need to be replaced

a new value or a vector of new values that willreplace the old values

Ifsilent = FALSE, a message will be printed regardinghow many values were replaced. Ifsilent = TRUE, no messagewill be printed regarding how many values were replaced. (default = FALSE)

a data object (a data frame or a data.table)

a formula object for the regression equation

number of significant digits to round to

round to nth digit after decimal(alternative tosigfigs)

number of bootstrap samples. The default is set at 1000,but consider increasing the number of samples to 5000, 10000, or aneven larger number, if slower handling time is not an issue.

a numeric vector

number of significant digits to flexibly round to.By default,sigfigs = 3.

a data object (a data frame or a data.table)

name of the variable that will go on the x axis

name of the variable that will go on the y axis

should the correlation be printed in theconsole? (default = TRUE)

name of the variable that will be used tolabel individual observations

name of the variable by which to weightthe individual observations for calculating correlation and plottingthe line of fit

opacity of the dots (0 = completely transparent,1 = completely opaque)

ifTRUE, the correlation and p-value willbe annotated at the top of the plot (default = TRUE)

position of the annotated stats, expressedas a percentage of the range of y values by which the annotatedstats will be placed above the maximum value of y in the data set(default = 5). This value will be determined relative to the data.Ifannotate_y_pos_rel = 5, and the minimum andmaximum y values in the data set are 0 and 100, respectively,the annotated stats will be placed at 5% of the y range (100 - 0)above the maximum y value, y = 0.05 * (100 - 0) + 100 = 105.

as an alternative to the argumentannotate_y_pos_rel, the input for this argument will determine theposition of the annotated stats. Ifannotate_y_pos_abs = 7.5,then the annotated stats will be placed at the y coordinate of 7.5.By default, this argument will be ignored unless it receives an input.That is, by default, the function will use the default value oftheannotate_y_pos_rel argument to determine the y coordinateof the annotated stats.

color of the annotated stats(default = "green4").

font size of the annotated stats(default = 6).

font face of the annotated stats(default = "bold").

ifline_of_fit_type = "lm", a regressionline will be fit; ifline_of_fit_type = "loess", a localregression line will be fit; ifline_of_fit_type = "none",no line will be fit

ifci_for_line_of_fit = TRUE,confidence interval for the line of fit will be shaded

color of the line of fit (default = "blue")

thickness of the line of fit (default = 1)

color of the dots (default = "black")

alternative label for the x axis

alternative label for the y axis

a numeric vector indicating thepositions of the tick marks on the x axis

a numeric vector indicating thepositions of the tick marks on the y axis

size of the dots on the plot (default = 2)

size for dots' labels on the plot. If noinput is entered for this argument, it will be set asdot_label_size = 5 by default. If the plot is to beweighted by some variable, this argument will be ignored, anddot sizes will be determined by the argumentdot_size_range

minimum and maximum size for dotson the plot when they are weighted

horizontally and vertically jitter dotsby a percentage of the respective ranges of x and y values.

horizontally jitter dots by a percentage of therange of x values.

vertically jitter dots by a percentage of therange of y values

logical. Should the axis lines be capped at theouter tick marks? (default = TRUE)

name of the variable that will determinecolors of the dots

name of the PNG file to be saved. By default, the namewill be "scatterplot_" followed by a timestamp of thecurrent time.The timestamp will be in the format, jan_01_2021_1300_10_000001,where "jan_01_2021" would indicate January 01, 2021;1300 would indicate 13:00 (i.e., 1 PM); and 10_000001 wouldindicate 10.000001 seconds after the hour.

ifsave = TRUE, the plot will be savedas a PNG file.

width of the plot to be saved. This argument will bedirectly entered as thewidth argument for theggsavefunction withinggplot2 package (default = 16)

height of the plot to be saved. This argument will bedirectly entered as theheight argument for theggsavefunction withinggplot2 package (default = 9)

a list of scale items (i.e., list of vectors of ratings)to code normally (as opposed to reverse coding).

a list of scale items to reverse code.

ifoperation = "mean", mean of the scale itemswill be calculated; ifoperation = "sum", sum of the scale itemswill be calculated (default = "mean").

logical. Thena.rm argument that will be passedonto the base R'srowMeans orrowSums function (default = FALSE).

logical. Ifna_summary = TRUE a summary ofNA values will be printed; ifna_summary = FALSE the summarywill not be printed (default = TRUE).

required for reverse coding; the numberfrom which to subtract item ratings when reverse-coding. For example,if the items to reverse code are measured on a 7-point scale, enterreverse_code_minuend = 8.

a numeric vector

Deprecated. By default, NA values will be removedbefore calculation

ifTRUE, notify how many observationswere removed due to missing values. By default, NA count will be printedonly if there are any NA values.

a vector of percentages; each of the percentage valuesmust be between 0 and 100

a vector of sample sizes; number of observations usedto calculate each of the percentage values

a vector of proportions; each of the proportion valuesmust be between 0 and 1

a vector of sample sizes; number of observations usedto calculate each of the percentage values

ifTRUE, clear the console (default = TRUE)

ifTRUE, remove all objects in theglobal environment (default = TRUE)

ifTRUE, set the workingdirectory to the active document in RStudio (default = TRUE)

ifTRUE, unload and load the kim package(default = TRUE)

a data object (a data frame or a data.table)

name of the dependent variable (DV)

name of the first independent variable (IV1), whosemain effects will be examined in the first set of contrasts

name of the second independent variable (IV2), whosesimple effects at each level of IV1 will be examined in the second setof contrasts

ordered levels of IV1

ordered levels of IV2

Ifprint_contrast_table = "weights_sums_and_products", contrasts'weights, sums of the weights and products will be printed. Ifprint_contrast_table = "weights_only", only the contrasts willbe printed.

output can be one of the following:"lm_object","table","weights_only","weights_sums_and_products","all" By default,output = NULL, and there will be nooutput from the function other than the tables of simple effects andconstrasts which will be printed on the console by default.

a data object (a data frame or a data.table)

name of the independent variable (IV)

name of the dependent variable (DV)

name of the moderator variable (MOD)

number of decimal places to which to roundthe focal values (default = 2)

number of decimal places to which to roundcoefficients from the regression analysis (default = 2)

number of decimal places to which to roundstandard error values from the regression analysis (default = 2)

number of decimal places to which to roundt statistics from the regression analysis (default = 2)

number of decimal places to which to roundp values from the regression analysis (default = 2)

this input will be used only in cases wheremoderator is continuous. In such cases, what are the focal valuesof the moderator at which to estimate the effect of IV on DV?By default, values corresponding to the mean of MOD, andmean of MOD +/-1 SD will be used.

a data object (a data frame or a data.table)

name of the independent variable (IV)

name of the dependent variable (DV)

name of the moderator variable (MOD)

number of decimal places to which to roundcoefficients from the regression analysis (default = 2)

number of decimal places to which to roundstandard error values from the regression analysis (default = 2)

number of decimal places to which to roundt statistics from the regression analysis (default = 2)

number of decimal places to which to roundp values from the regression analysis (default = 2)

this input will be used only in cases where MODis continuous. In such cases, what are the focal values of the MODat which to estimate the effect of IV on DV? By default, valuescorresponding to the mean of MOD, and mean of MOD +/-1 SD will be used.

a numeric vector

a character string indicating the type of skewness tocalculate. Iftype = "adjusted", the adjusted Fisher-Pearsonstandardized moment coefficient will be calculated. Iftype = "traditional", the traditional Fisher-Pearsoncoefficient of skewness will be calculated. Iftype = "pearson_2",the Pearson 2 skewness coefficient will be calculated. By default,type = "adjusted".

a data object (a data frame or a data.table)

name of the binary independent variable (IV)

name of the dependent variable (DV)

name of the continuous moderator variable (MOD)

logical. Should logistic regressions be conducted,rather than ordinary least squares regressions? By default,ordinary least squares regressions will be conducted.

name(s) of the variable(s) to control for inestimating conditional values of the DV.

focal values of the moderator variable at whichto estimate IV's effect on DV.

logical. Should the plot include ap-value for the interaction term?

order of levels in the independentvariable for legend. By default, it will be set as levels of theindependent variable ordered using R's base functionsort.

type of output (default = "plot"). Otherpossible values include "spotlight_results", "dt_for_plotting","modified_dt"

set colors for the two levels of the independent variableBy default,colors = c("red", "blue").

size of the observed_dots (default = 3)

logical. Ifobserved_dots = TRUE, theobserved values of all IV, DV, and MOD combinations will be plotted asdots. On top of these dots the spotlight analysis plot will be laid.Ifobserved_dots = FALSE, these dots will not be plotted.By default,observed_dots = FALSE.

logical. Ifreg_lines = TRUE, the regressionlines from regressing DV on MOD at each value of IV will be plotted.Ifreg_lines = FALSE, these regression lines will not be plotted.By default,observed_dots = FALSE.

thickness of the regression lines (default = 1).

deprecated. Usereg_line_width instead.thickness of the regression lines (default = 1).

logical. Should lines connecting theestimated values of DV be drawn? (default = TRUE)

thickness of the lines connectingthe estimated values of DV (default = 1).

ggplot value for shape of the dotsat estimated values of DV (default = 15, a square shape).

size of the dots at estimated values ofDV (default = 6).

iferror_bar = "se"; error bars will be +/-1standard error, iferror_bar = "ci" error bars will be aconfidence interval. By default,error_bar = "ci".

width of the confidence interval(default = 0.95 for a 95 percent confidence interval).This argument will not apply whenerror_bar = "se"

graphically, width of the segmentsat the end of error bars (default = 0.13)

(default)

thickness of the error bars (default = 1)

(default)

(default)

(default)

(default)

(default)

(default)

(default)

(default)

(default)

(default)

(default)

The first part of the text forlabeling simple effects.By default,simp_eff_text_part_1 = "Simple Effect\n"

color for the text indicating p-valuesof simple effects (default = "black").

font size of the text indicatingp-values of simple effects (default = 5).

(default)

(default)

font size for the interactionp value (default = 6)

(default)

(default)

(default)

(default)

(default)

(default)

(default)

(default)

(default)

(default)

title of the x axis. By default, it will be setas input formod_name. Ifx_axis_title = FALSE, it willbe removed.

title of the y axis. By default, it will be setas input fordv_name. Ify_axis_title = FALSE, it willbe removed.

title of the legend. By default, it will be setas input foriv_name. Iflegend_title = FALSE, it willbe removed.

position of the legend (default = "right").Iflegend_position = "none", the legend will be removed.

position of the y axis title (default = 0.85).If default is used,y_axis_title_vjust = 0.85, the y axis titlewill be positioned at 85% of the way up from the bottom of the plot.

To how many digits after thedecimal point should the p value for the interaction term berounded? (default = 3)

horizontally jitter dots by a percentage of therange of x values

vertically jitter dots by a percentage of therange of y values

opacity of the dots (0 = completely transparent,1 = completely opaque). By default,dot_alpha = 0.2

(default)

(default)

types of the regression lines for the two levelsof the independent variable.By default,reg_line_types = c("solid", "dashed")

(default)

margin for the plotBy defaultplot_margin = ggplot2::unit(c(60, 30, 7, 7), "pt")

Ifsilent = FALSE, (various) messages will beprinted. Ifsilent = TRUE, the messages will be suppressed.By default,silent = FALSE.

a numeric vector

a data object (a data frame or a data.table)

a formula object for the regression equation

names of binary variables to reverse code

number of significant digits to round to

round to nth digit after decimal(alternative tosigfigs)

number of decimal places to which to round p-values(default = 3)

logical. Should the p-values be roundedin a pretty format (i.e., lower threshold: "<.001").By default,pretty_round_p_value = TRUE.

logical. Should only the upper partof the table be returned?By default,return_table_upper_half = FALSE.

number of digits after the decimal both r-squaredand adjusted r-squared values should be rounded to (default 3)

number of digits after the decimal the f statisticof the regression model should be rounded to (default 2)

logical. Should the column namesof the regression table be made pretty (e.g., change "std_beta" to"Std. Beta")? (Default =TRUE)

Ifupdate = "force", force updating the package'kim'. Ifupdate = TRUE, compares the currently installed package'kim' with the most recent version on GitHub and, if the version on GitHubis more recent, ask the user to confirm the update. If confirmed,then update the package. Ifupdate = FALSE, skip updatingthe package. By default,update = "force"

input for theupgrade argument tobe passed on toremotes::install_github.One of "default", "ask", "always", "never", TRUE, or FALSE."default" respects the value of the R_REMOTES_UPGRADE environmentvariable if set, and falls back to "ask" if unset."ask" prompts the user for which out of date packages to upgrade.For non-interactive sessions "ask" is equivalent to "always".TRUE and FALSE correspond to "always" and "never" respectively.By default,upgrade_other_pkg = FALSE.

logical. Ifupdate = TRUE, runs the functionsetup_r_env in the package "kim". Type "?kim::setup_r_env" to learn more.By default,setup_r_env = TRUE

a vector of names of packages to load and attach.By default,default_packages = c("data.table", "ggplot2")

a character vector indicating names ofpackages to load silently (i.e., suppress messages that get printedwhen loading the packages).By default,silent_load_pkgs = c("data.table", "ggplot2")

a vector or a data frame or an array or NULL.

an argument to be passed onto the 'sort' function(in base R) for controlling the treatment of NA values.Ifna.last = TRUE, NA values in the data are put last;ifna.last = FALSE, NA values are put first;ifna.last = NA, NA values are removed.By default,na.last = TRUE

logical. Should the sort be increasing or decreasing?An argument to be passed onto the 'sort' function (in base R).By default,decreasing = FALSE

a data object (a data frame or a data.table)

name of the independent variable

name of the dependent variable

number of significant digits to round to

Should Welch's t-tests be conducted?By default,welch = TRUE

ifcohen_d = TRUE, Cohen's d statistics will beincluded in the output data.table.

ifcohen_d_w_ci = TRUE,Cohen's d with 95% CI will be included in the output data.table.

the name of the method to use to adjust p-values.Ifadjust_p = "holm", the Holm method will be used;ifadjust_p = "bonferroni", the Bonferroni method will be used.By default,adjust_p = "holm"

The use of this argument is deprecated.Use the 'adjust_p' argument instead.Ifbonferroni = TRUE, Bonferroni tests will beconducted for t-tests or Mann-Whitney tests.

ifTRUE, Mann-Whitney test results will beincluded in the output data.table. IfFALSE, Mann-Whitneytests will not be performed.

this is the input for the 'exact'argument used in the 'stats::wilcox.test' function, whichconducts a Mann-Whitney test. By default,mann_whitney_exact = FALSE. If you want to use the default settingsfor the 'stats::wilcox.test' function, consider settingmann_whitney_exact = TRUE.

ift_test_stats = TRUE, t-test statisticand degrees of freedom will be included in the output data.table.By default,t_test_stats = TRUE

ifsd = TRUE, standard deviations will beincluded in the output data.table.

number of decimal places to which to roundp-values (default = 3)

Should a one-way ANOVA be conducted and reported?By default,anova = FALSE, but when there are more than twolevels in the independent variable, the value will change such tatanova = TRUE.

number of decimal places to which to roundthe f statistic (default = 2)

number of decimal places to which to roundthe t statistic (default = 2)

number of decimal places to which to roundthe degrees of freedom for t tests (default = 2)