The goal offreqtables is to quickly make tables ofdescriptive statistics for categorical variables (i.e., counts,percentages, confidence intervals). This package is designed to work inatidyverse pipeline, and consideration has been given toget results from R to Microsoft Word ® with minimal pain.
You can install the released version offreqtables fromCRAN with:
install.packages("freqtables")And the development version fromGitHub with:
# install.packages("devtools")devtools::install_github("brad-cannell/freqtables")Becausefreqtables is intended to be used in adplyr pipeline, loadingdplyr into yourcurrent R session is recommended.
library(dplyr)library(freqtables)The examples below will use R’s built-inmtcars dataset.
data("mtcars")Thefreq_table() function produces one-way and two-wayfrequency tables for categorical variables. In addition to frequencies,thefreq_table() function displays percentages, and thestandard errors and confidence intervals of the percentages. For two-waytables only,freq_table() also displays row (subgroup)percentages, standard errors, and confidence intervals.
For one-way tables, the default 95 percent confidence intervalsdisplayed are logit transformed confidence intervals equivalent to thoseused by Stata. Additionally,freq_table() will return Wald(“linear”) confidence intervals if the argument to ci_type = “wald”.
For two-way tables,freq_table() returns logittransformed confidence intervals equivalent to those used by Stata.
Here is an example of usingfreq_table() to create aone-way frequency table with all function arguments left at theirdefault values:
mtcars%>%freq_table(am)#> var cat n n_total percent se t_crit lcl ucl#> 1 am 0 19 32 59.375 8.820997 2.039513 40.94225 75.49765#> 2 am 1 13 32 40.625 8.820997 2.039513 24.50235 59.05775Here is an example of usingfreq_table() to create atwo-way frequency table with all function arguments left at theirdefault values:
mtcars%>%freq_table(am, cyl)#> # A tibble: 6 × 17#> row_var row_cat col_var col_cat n n_row n_total percent_total se_total#> <chr> <chr> <chr> <chr> <int> <int> <int> <dbl> <dbl>#> 1 am 0 cyl 4 3 19 32 9.38 5.24#> 2 am 0 cyl 6 4 19 32 12.5 5.94#> 3 am 0 cyl 8 12 19 32 37.5 8.70#> 4 am 1 cyl 4 8 13 32 25 7.78#> 5 am 1 cyl 6 3 13 32 9.38 5.24#> 6 am 1 cyl 8 2 13 32 6.25 4.35#> # … with 8 more variables: t_crit_total <dbl>, lcl_total <dbl>,#> # ucl_total <dbl>, percent_row <dbl>, se_row <dbl>, t_crit_row <dbl>,#> # lcl_row <dbl>, ucl_row <dbl>You can learn more about thefreq_table() function andways to adjust default behaviors invignette(“descriptive_analysis”).
Thefreq_test() function is an S3 generic. It currentlyhas methods for conducting hypothesis tests on one-way and two-wayfrequency tables. Further, it is made to work in a dplyr pipeline withthefreq_table() function.
For thefreq_table_two_way class, the methods used arePearson’s chi-square test of independence Fisher’s exact test. When cellcounts are <= 5, Fisher’s Exact Test is considered more reliable.
Here is an example of usingfreq_test() to test theequality of proportions on a one-way frequency table with all functionarguments left at their default values:
mtcars%>%freq_table(am)%>%freq_test()%>%select(var:percent, p_chi2_pearson)#> var cat n n_total percent p_chi2_pearson#> 1 am 0 19 32 59.375 0.2888444#> 2 am 1 13 32 40.625 0.2888444Here is an example of usingfreq_test() to conduct achi-square test of independence on a two-way frequency table with allfunction arguments left at their default values:
mtcars%>%freq_table(am, vs)%>%freq_test()%>%select(row_var:n, percent_row, p_chi2_pearson)#> # A tibble: 4 × 7#> row_var row_cat col_var col_cat n percent_row p_chi2_pearson#> <chr> <chr> <chr> <chr> <int> <dbl> <dbl>#> 1 am 0 vs 0 12 63.2 0.341#> 2 am 0 vs 1 7 36.8 0.341#> 3 am 1 vs 0 6 46.2 0.341#> 4 am 1 vs 1 7 53.8 0.341You can learn more about thefreq_table() function andways to adjust default behaviors in vignette(“using_freq_test”).
The freq_format function is intended to make it quick and easy toformat the output of the freq_table function for tables that may be usedfor publication. For example, a proportion and 95% confidence intervalcould be formatted as “24.00 (21.00 - 27.00).”
mtcars%>%freq_table(am)%>%freq_format(recipe ="percent (lcl - ucl)",name ="percent_95",digits =2 )%>%select(var, cat, percent_95)#> var cat percent_95#> 1 am 0 59.38 (40.94 - 75.50)#> 2 am 1 40.62 (24.50 - 59.06)You can learn more about thefreq_format() function byreading the function documentation.