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Multilevel Multivariate Meta-analysis with Application to Choice Overload

Published online by Cambridge University Press:  01 January 2025

Blakeley B. McShane  and
Ulf Böckenholt
Blakeley B. McShane*
Affiliation:
Northwestern University
Ulf Böckenholt
Affiliation:
Northwestern University
*
Correspondence should be made toBlakeleyB.McShane,Kellogg School of Management, NorthwesternUniversity, Evanston, IL 60208, USA. Email: [email protected]
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Abstract

We introduce multilevel multivariate meta-analysis methodology designed to account for the complexity of contemporary psychological research data. Our methodology directly models the observations from a set of studies in a manner that accounts for the variation and covariation induced by the facts that observations differ in their dependent measures and moderators and are nested within, for example, papers, studies, groups of subjects, and study conditions. Our methodology is motivated by data from papers and studies of the choice overload hypothesis. It more fully accounts for the complexity of choice overload data relative to two prior meta-analyses and thus provides richer insight. In particular, it shows that choice overload varies substantially as a function of the six dependent measures and four moderators examined in the domain and that there are potentially interesting and theoretically important interactions among them. It also shows that the various dependent measures have differing levels of variation and that levels up to and including the highest (i.e., the fifth, or paper, level) are necessary to capture the variation and covariation induced by the nesting structure. Our results have substantial implications for future studies of choice overload.

Keywords

multilevelmultivariatemeta-analysischoiceoverload
Type
Original Paper
Information
Psychometrika , Volume 83 , Issue 1 , March 2018 , pp. 255 - 271
Copyright
Copyright © 2017 The Psychometric Society

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Footnotes

The authors thank Alex Chernev for his encouragement and support of this article. Supplementary materials for this article are available online at http://www.blakemcshane.com/research.

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