How many countries for multilevel modeling? A comparison of frequentist and bayesian approaches

Published

Journal Article

Researchers in comparative research increasingly use multilevel models to test effects of country-level factors on individual behavior and preferences. However, the asymptotic justification of widely employed estimation strategies presumes large samples and applications in comparative politics routinely involve only a small number of countries. Thus, researchers and reviewers often wonder if these models are applicable at all. In other words, how many countries do we need for multilevel modeling? I present results from a large-scale Monte Carlo experiment comparing the performance of multilevel models when few countries are available. I find that maximum likelihood estimates and confidence intervals can be severely biased, especially in models including cross-level interactions. In contrast, the Bayesian approach proves to be far more robust and yields considerably more conservative tests. ©2013, Midwest Political Science Association.

Full Text

Duke Authors

Cited Authors

  • Stegmueller, D

Published Date

  • January 1, 2013

Published In

Volume / Issue

  • 57 / 3

Start / End Page

  • 748 - 761

Electronic International Standard Serial Number (EISSN)

  • 1540-5907

International Standard Serial Number (ISSN)

  • 0092-5853

Digital Object Identifier (DOI)

  • 10.1111/ajps.12001

Citation Source

  • Scopus