Micro–Macro Multilevel Analysis for Discrete Data A Latent Variable Approach and an Application on Personal Network Data

• Published in: Sociological methods & research Vol. 42; no. 4; pp. 431 - 457
• Main Authors: Bennink, Margot, Croon, Marcel A., Vermunt, Jeroen K.
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01.11.2013; SAGE PUBLICATIONS, INC
• Subjects: Linear models; Marriage; Multidimensional analysis; Power; Probability; Regression analysis; Religion; Simulation; Social Networks; Sociological methodology; Sociology; Variables; multilevel analysis; micro–macro analysis; marriage; generalized linear modeling; personal network; level-2 outcome; latent class analysis; latent variable; religion
• ISSN: 0049-1241; 1552-8294
• DOI: 10.1177/0049124113500479

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.