Comments on "correspondence analysis makes you blind"

TL;DR

This paper discusses the impact of correspondence analysis on data interpretation, proposing a new framework that decomposes covariance and density matrices to provide dual maps for better understanding contingency tables.

Contribution

It introduces a taxicab correspondence analysis framework that simultaneously decomposes covariance and density matrices, offering a novel interpretative approach for contingency tables.

Findings

Provides dual maps for contingency table analysis

Enhances interpretability of correspondence analysis

Proposes a new framework for data decomposition

Abstract

Collins' (2002) statement "correspondence analysis makes you blind" followed after his seriation like description of a brand attribute count data set analyzed by Whitlark and Smith (2001), who applied correspondence analysis. In this essay we comment on Collins' statement within taxicab correspondence analysis framework by simultaneously decomposing the covariance matrix and its associated density matrix, thus interpreting two interrelated maps for contingency tables : TCov map and TCA map.