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Should I Use Fixed or Random Effects?

Published online by Cambridge University Press:  21 November 2014

Tom S. Clark  and
Drew A. Linzer
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Abstract

Empirical analyses in social science frequently confront quantitative datathat are clustered or grouped. To account for group-level variation andimprove model fit, researchers will commonly specify either a fixed- orrandom-effects model. But current advice on which approach should bepreferred, and under what conditions, remains vague and sometimescontradictory. This study performs a series of Monte Carlo simulations toevaluate the total error due to bias and variance in the inferences of eachmodel, for typical sizes and types of datasets encountered in appliedresearch. The results offer a typology of dataset characteristics to helpresearchers choose a preferred model.

Information

Type
Original Articles
Information
Political Science Research and Methods , Volume 3 , Issue 2 , May 2015 , pp. 399 - 408
Copyright
Copyright © The European Political Science Association 2014 

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Footnotes

*

Tom Clark is Asa Griggs Candler Professor of Political Science, EmoryUniversity, 1555 Dickey Drive, Atlanta, GA 30030 USA (email: tom.clark@emory.edu). Drew Linzer isAssistant Professor, Department of Political Science, Emory University(email: drew@votamatic.org). Wethank Kyle Beardsley, Justin Esarey, Andrew Gelman, Kosuke Imai,Benjamin Lauderdale, Jeffrey Lax and Jamie Monogan for helpfuldiscussions and feedback. Nigel Lo provided valuable researchassistance.

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Clark and Linzer Dataset

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http://dx.doi.org/10.7910/DVN/25588
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