hce package. The standardizedoutput object is now of classadhce. This means also thatthere is a more standardized output that make it easier to work with. Asa result, themaraca package has now a higherhce version dependency (0.8.5). Also, all class dependentfunctions in the package have been updated to only work on theadhce class object (for exampleplot.adhce()).remove_outliers inplot.maraca() andplot.adhce(). In some cases,there might be outliers that skew the displayed range for the continuousendpoint. There is now an option to display the continuous endpointwithout the outliers by setting the parameterremove_outliers = TRUE in theplot.maraca() orplot.adhce() function. We define outliers here according tothe common boxplot calculation definition: any data outside the range25th percentile - 1.5 * IQR (inter-quartile range) and 75th percentile +1.5 * IQR. Note that this required some refactoring in how the plot isconstructed. Especially the violin plot is now pre-calculated and thenplotted using theggplot2 functiongeom_polygon() (rather than thegeom_violin()function).density_plot_type = "box" is selected, theboxplot will now contain vertical segments to indicate where thewhiskers end.animate_maraca() function. This is an animated version ofthe standard maraca plot to allow to show how the plot is being built upstep-by-step. Note that thegganimate package needs to beinstalled to create the animation. Additionally, to save the animationas a gif, the packagegifski needs to be installed. This isan experimental feature, so despite doing some testing duringdevelopment there might be some problems or unexpected behavior duringusage. Please take a minute to report any wrong behavior to allow us toimprove the functionality.Slight change in automatic checks after an update of thehce package (dependency).
mosaic_plot - a new plot to comparesoutcome between an active treatment group and a control group,highlighting areas of “Wins”, “Losses” and “Ties” based on endpointhierarchy. Details are given in the new vignette “Maraca Plots -Introduction to the Mosaic plot”.cumulative_plot()function -dustin() anddustin_plot().Updated author information.
component_plot(), there has been anew plot added calledcumulative_plot(). As opposed to theprevious plot showing the individual components of the win oddscomputation, this plot is displaying the endpoints cumulated instead(adding one component of hierarchical endpoint at a time). Details canbe found in the vignette “Maraca Plots - Plotting win odds”.tte_outcomes has been changed tostep_outcomes and the parametercontinuous_outcome tolast_outcome.ggplot2 is now automatically attached when loadingmaraca.maraca has a new dependency - thepatchwork package.trans parameter in the plotting functions was notworking as intended. It now enables x-axis transformation for thecontinuous endpoint part of the plot.theme argument in the plotting functions allowsusers to easily change the styling of the plot. Details are given in thenew vignette “Maraca Plots - Themes and Styling”.component_plot() function works for bothmaraca andhce. Details can be found in thenew vignette “Maraca Plots - Plotting win odds”.validate_maraca() that was added in version0.5.maraca now has increased the version dependency for thepackagehce to >= 0.5.hce package is now automatically attached whenloadingmaraca.print() function for maraca objects that summarizes keyinformation.validate_maraca() function that extracts keyinformation from a maraca plot object. This can be used to validate theplot against independently coded versions (for example using a differentprogramming language).maraca() function now requires an input for theparameterfixed_followup_days. Note that there can be noobserved events in the data after the follow-up time specified.maraca does no longer depend on thegridExtra package.plot_tte_components() function for plotting theindividual time-to-event outcomes was removed from the package since itdid not prove to be overly useful.plot_tte_composite() was removed for now since thepackage cannot correctly calculate the composite version of looking atmultiple time-to-event endpoints when patients have multipleevents.