AN APPLICATION OF THE MIXED EFFECTS TREND VECTOR MODELS TO THE ANALYSIS OF ASYMMETRIC SQUARE CONTINGENCY TABLES WITH AUXILIARY VARIABLES

• Published in: Behaviormetrika Vol. 39; no. 1; pp. 75 - 90
• Main Author: Rooij, Mark de
• Format: Journal Article
• Language: English
• Published: Tokyo The Behaviormetric Society 2012; Springer Japan; Springer Nature B.V
• Subjects: Asymmetry; biplots; categorical data; Chemistry and Earth Sciences; Computer Science; Contingency; Data processing; Economics; Finance; Gauss-Hermite quadrature; Insurance; Management; multi-dimensional scaling; multilevel model; Physics; Statistical analysis; Statistical Theory and Methods; Statistics; Statistics for Business; Statistics for Engineering; categorical data; multilevel model; multidimensional scaling; biplots; Gauss-Hermite quadrature
• ISSN: 0385-7417; 1349-6964
• DOI: 10.2333/bhmk.39.75

We propose to use the mixed effect trend vector model for modeling of repeated multinomial choice data in the form of a square contingency table. Such data often shows asymmetries where more people change from category a to b than the other way around. In many cases an investigator has, besides the actual choices of the participants, auxiliary variables that pertain to the subjects under study. Most methodologies for asymmetric data do not take into account such variables. We will show how to incorporate these auxiliary variables into the mixed effects trend vector model and how they can be used to study differential change. The models are illustrated in detail with data from the Dutch parliamentary election studies 2006.