journal article
LitStream Collection
The analysis of structured qualitative data
1999 Applied Stochastic Models and Data Analysis
doi: 10.1002/(SICI)1099-0747(199903)15:1<1::AID-ASM356>3.0.CO;2-F
The aim of this paper is to give an overview of the methodological contribution given by Italian researchers in introducing a priori information into multidimensional data analysis techniques, paying special attention to categorical variables. The basic method is Non‐Symmetrical Correspondence Analysis, which enables the analysis of a contingency table when the behaviour of one variable is supposed to be dependent on the other cross‐classified variable. As usual correspondence analysis decomposes an association index (Pearson's Φ2), in a principal component sense, the proposed method is based on a decomposition of a predictability index (Goodman and Kruskal's τb).