Analysis Of Categorical Data With R May 2026

Visual tools help identify patterns and relationships between categories.

: Functions like factor() or as.factor() convert character vectors into categorical variables.

: Specialized for working with factors and reordering levels. Analysis of categorical data with R

: Provides functions for multivariate categorical data analysis using the Akaike Information Criterion (AIC). Categorical Data Descriptive Statistics

: The table() function generates counts for each category. Analysis of categorical data with R

For more advanced categorical analysis, these packages are widely used:

: For binary outcomes (e.g., "Success/Failure"), the glm() function with family = binomial is the standard for modeling how predictors influence the probability of an outcome. Analysis of categorical data with R

: Provides advanced tools for visualizing categorical data, including mosaic and association plots. confreq : Designed for Configural Frequency Analysis (CFA).