NOW AVAILABLE: Essentials of Poltical Analysis 7e | R Companion 4e | SPSS 7e | Stata 5e | Excel 1e 🎵
NOW AVAILABLE: Essentials 7e | R Companion 4e | SPSS 7e | Stata 5e | Excel 1e 🎵
NOW AVAILABLE: Essentials 7e | More Textbooks 🎵
If this link is broken, please
You can also
(will be reviewed).

Small Country Samples: Why Bayesian Wins Over Frequentist Multilevel Models

Comparative research often uses multilevel models to study how country-level factors affect individual behaviors. However, these traditional estimation methods face challenges when data includes only a few countries.

➡️ How Few Countries Work:

A large-scale Monte Carlo experiment reveals that maximum likelihood estimates can be severely biased with limited country samples, particularly in models featuring cross-level interactions.

➡️ Bayesian Solution:

Bayesian approaches demonstrate much greater robustness and provide more conservative test results even when the number of countries is small.

➡️ The Takeaway:

Researchers should consider using Bayesian methods for multilevel analyses involving few countries to improve reliability.

American Journal of Political Science
How Many Countries for Multilevel Modeling? A Comparison of Frequentist and Bayesian Approaches. was authored by Daniel Stegmueller. It was published in AJPS in 2013. Find on Google Scholar10.1111/ajps.12001
Methodology subfield banner