Changelog • statsreportr

statsreportr (development version)

report_pc() now supports the group argument to specify grouping variables to filter the pairwise comparisons.

report_pc() now takes into consideration the order of named effect argument to determine the direction of the effect size in the output.

report_pc() now is able to report effect sizes for pairwise comparisons. The effect size is calculated using the emmeans::eff_size() function.

cor_test() and report_cor() added to the package. These functions are used to report the results of correlation tests. cor_test() is modified version of rstatix::cor_test() that will save the degrees of freedom of a Pearson correlation in the output, and report_cor() formats the results for reporting in R Markdown and Quarto documents.

report_pc() added to the package. This function is used to report the results of a pairwise comparison test. It is designed to be used in conjunction with the function emmeans_test() from the ‘rstatix’ R package, and to be used in inline r code within R Markdown and Quarto documents.

report_mean_sd() and report_mean_sem() added to the package. These functions are used to report the mean and standard deviation or standard error of a dataset, respectively. They are designed to be used in inline r code within R Markdown and Quarto documents.

report_anova() and report_t() added to the package. These functions are used to report the results of ANOVA and t-tests, respectively. They are designed to be used in conjunction with the functions anova_test() and t_test() from the ‘rstatix’ R package, and to be used in inline r code within R Markdown and Quarto documents. report_anova() also works with aov() objects by running rstatix::anova_summary() on the object before reporting the results.
format_p() added to the package. This function is used to format p-values in a report-ready format. It is mainly used to format the p-values within the report_*() functions, but is available for use in other contexts as well.