Correspondence analysis (CA) is a quantitative data analysis method that offers researchers a visual understanding of relationships between qualitative (i.e., categorical) variables. Even though CA [Page 276]closely relates to the chi-square statistic (χ²), it is not an inferential method for directly testing theory and hypotheses. Instead, CA is a descriptive data reduction technique, similar to principal components analysis (PCA). Performing a CA using computer software offers researchers an easy way to interpret graphic representation of cross-tabulated data appearing in contingency tables. As widely used statistical methods seldom consider relationships between categorical variables, many such relationships go unnoticed in datasets. Although CA is a descriptive method, identification of any such previously unnoticed relationships can lead to future hypothesis testing. This entry provides background on ...
Looks like you do not have access to this content.