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.