Visual tools help identify patterns and relationships between categories.
: Display changes or flows between categorical variables over time using the ggalluvial package . Inferential Statistics and Modeling 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). confreq : Designed for Configural Frequency Analysis (CFA)
Analysis of categorical data in R involves specialized techniques for variables that represent qualitative characteristics, such as gender, region, or recovery status. Unlike continuous numerical data, categorical data—referred to as in R—is divided into discrete groups or "levels". Data Representation and Handling Data Representation and Handling In R, categorical data
In R, categorical data is stored using the factor class. While string variables can be treated as text, converting them to factors ensures they are correctly interpreted in statistical models.
Inferential methods allow researchers to test hypotheses about categorical relationships in a population.