Post Component Analysis of Categorical data
U. Sangeetha · IOSR Journal of Mathematics · 2013
Categorical data are often stratified into two dimensional I × J tables in order to test the independence of attributes.Agresti (1999) has discussed testing methods with partitioning property of chi square to extract components that describe certain aspects of the overall association in a table.In this work an attempt has been made to study the pattern in which sub-tables exhibit a sign of reverse association when compared to a significant association of attributes with regard to the original I × J table.Simulation studies and subsequent results of vote counting method indicate that 2 × 2 tables have the reversal component association when compared to higher order sub-tables; interestingly, in more than 90% cases.The computationally extensive and exhaustive procedure provide a better tool to understand the association between the categories that focus on the strongest differences among all comparisons, and could be practically and other aspects in experimental studies such as clinical trials.