Multilevel Models for the Analysis of Comparative Survey Data: Common Problems and Some Solutions; [Mehrebenenmodelle zur Analyse von vergleichenden Umfragedaten: Häufige Probleme und ausgewählte Lösungsansätze]

This paper provides an overview over the application of mixed models (multilevel models) to comparative survey data where the context units of interest are countries. Such analyses have gained much popularity in the last two decades but they also come with a variety of challenges, some of which are discussed here. A focus lies on the small-N problem, influential cases (outliers) and the issue of omitted variables at the country level. Summarizing the methodological literature, the paper provides recommendations for applied researchers when possible or otherwise points to the more detailed literature. Some solutions for the small-N problem and omitted variable bias are discussed in detail, recommending the pooling of multiple survey waves to increase statistical power and to allow for the estimation of within-country effects, thereby controlling for unobserved heterogeneity. All issues are illustrated using an empirical example with data from the European Social Survey. The online appendix provides detailed syntax to adopt the presented procedures to researchers’ own data. © 2019, Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature.