Prof. Dr. Alexander W. Schmidt-Catran

Multilevel Models for the Analysis of Comparative Survey Data: Common Problems and Some Solutions

Online Appendix

Alexander W. Schmidt-Catran, Malcolm Fairbrother and Hans-Jürgen Andreß

Kölner Zeitschrift für Soziologie und Sozialpsychologie
Special Issue on International Comparative Social Research



Abstract

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.



Downloads

Download the online appendix (PDF with additional information and tables) here.



Download the replication file for stata (zip-file) here.



Download the coding of multilevel models in ESR (Excel-file) here.



Links

Valentin Velev has reproduced the analysis with R. Click here to find his markdown document with R code.



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