sjstats - Collection of Convenient Functions for Common Statistical Computations

Collection of convenient functions for common statistical computations, which are not directly provided by R’s base or stats packages.

This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like Cramer’s V, Phi, or effict size statistics like Eta or Omega squared), or for which currently no functions available.

Second, another focus lies on weighted variants of common statistical measures and tests like weighted standard error, mean, t-test, correlation, and more.

The comprised tools include:

• Especially for mixed models: design effect, sample size calculation
• Weighted statistics and tests for: mean, median, standard error, standard deviation, correlation, Chi-squared test, t-test, Mann-Whitney-U-test

Documentation

Please visit https://strengejacke.github.io/sjstats/ for documentation and vignettes.

Installation

Latest development build

To install the latest development snapshot (see latest changes below), type following commands into the R console:

library(devtools)
devtools::install_github("strengejacke/sjstats")

Officiale, stable release

To install the latest stable release from CRAN, type following command into the R console:

install.packages("sjstats")

Citation

In case you want / have to cite my package, please use citation('sjstats') for citation information.