Micro–Macro Multilevel Analysis for Discrete Data: A Latent Variable Approach and an Application on Personal Network Data. (November 2013)

• Record Type: Journal Article
• Authors: Bennink, Margot; Croon, Marcel A.; Vermunt, Jeroen K.
• Is Part Of: Sociological methods & research. Volume 42:Number 4(2013)
• Page Start: 431
• Page End: 457
• Publication Date: 2013-11
• Subjects: generalized linear modeling -- multilevel analysis -- level-2 outcome -- latent class analysis -- latent variable -- micro–macro analysis -- personal network -- marriage -- religion; Sociology -- Research -- Periodicals; Sociology -- Methodology -- Periodicals; 301.072
• DOI: 10.1177/0049124113500479
• Languages: English
• ISSNs: 0049-1241

Abstract

A multilevel regression model is proposed in which discrete individual-level variables are used as predictors of discrete group-level outcomes. It generalizes the model proposed by Croon and van Veldhoven for analyzing micro–macro relations with continuous variables by making use of a specific type of latent class model. A first simulation study shows that this approach performs better than more traditional aggregation and disaggreagtion procedures. A second simulation study shows that the proposed latent variable approach still works well in a more complex model, but that a larger number of level-2 units is needed to retain sufficient power. The more complex model is illustrated with an empirical example in which data from a personal network are used to analyze the interaction effect of being religious and surrounding yourself with married people on the probability of being married.