Abstract
Two analytical approaches for the nonequivalent control group design with categorical dependent variables. The statistical analysis of nonequivalent control group design (NECGD) with numerical dependent variables has been a exciting topic of research during the last decade. Much less interest has been demanded for the use of categorical dependent variables in the statistical analysis of the same design, but the main ideas remain. Nevertheless, some dificulties mainly due to measurement error in variables and omitted variables preclude a correct analysis. In this work we compare two recent approaches that may be efficiently used for the statistical analysis of NECGD: the multivariate model with repeated measures (Agresti, 1996, 1997) and the linear partial credit model (Fischer and Ponocny, 1994, 1995). We use a clinical example commenting the interpretation of results with these two approaches.
