Book review
In: Studies in conflict and terrorism, Band 18, Heft 3, S. 243-244
ISSN: 1521-0731
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In: Studies in conflict and terrorism, Band 18, Heft 3, S. 243-244
ISSN: 1521-0731
In: Conflict: an international journal for conflict and policy studies, Band 6, Heft 2, S. 97-115
ISSN: 0149-5941
World Affairs Online
In: Political analysis: PA ; the official journal of the Society for Political Methodology and the Political Methodology Section of the American Political Science Association, Band 30, Heft 1, S. 46-65
ISSN: 1476-4989
AbstractWhen working with grouped data, investigators may choose between "fixed effects" models (FE) with specialized (e.g., cluster-robust) standard errors, or "multilevel models" (MLMs) employing "random effects." We review the claims given in published works regarding this choice, then clarify how these approaches work and compare by showing that: (i) random effects employed in MLMs are simply "regularized" fixed effects; (ii) unmodified MLMs are consequently susceptible to bias—but there is a longstanding remedy; and (iii) the "default" MLM standard errors rely on narrow assumptions that can lead to undercoverage in many settings. Our review of over 100 papers using MLM in political science, education, and sociology show that these "known" concerns have been widely ignored in practice. We describe how to debias MLM's coefficient estimates, and provide an option to more flexibly estimate their standard errors. Most illuminating, once MLMs are adjusted in these two ways the point estimate and standard error for the target coefficient are exactly equal to those of the analogous FE model with cluster-robust standard errors. For investigators working with observational data and who are interested only in inference on the target coefficient, either approach is equally appropriate and preferable to uncorrected MLM.
World Affairs Online