Categorical Data Analysis

Includes wrapper functions around existing functions for the analysis of categorical data and introduces functions for calculating risk differences and matched odds ratios. R currently supports a wide variety of tools for the analysis of categorical data. However, many functions are spread across a variety of packages with differing syntax and poor compatibility with each another. prop_test() combines the functions binom.test(), prop.test() and BinomCI() into one output. prop_power() allows for power and sample size calculations for both balanced and unbalanced designs. riskdiff() is used for calculating risk differences and matched_or() is used for calculating matched odds ratios. For further information on methods used that are not documented in other packages see Nathan Mantel and William Haenszel (1959) and Alan Agresti (2002) .

catfun

catfun simplifies existing functions for categorical data analysis.

Installation

devtools::install_github("nt-williams/catfun")

What’s inside

R currently supports a wide variety of tools for the analysis of categorical data. However, many functions are spread across a variety of packages with differing syntax and poor compatibility with each another.

To address this issue, catfun includes wrapper functions around existing functions for tests of proportions, power analyses for proportions, and measures of association into one structure.

For example, prop_test() combines the base R functions binom.test(), prop.test() and BinomCI() from the DescTools package into one. The 3 mentioned functions all perform important aspects of testing for differences among proportions but are now used to create one output with all relevant information within one spot.