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Journal Article

Multilevel modelling of country effects: a cautionary tale

Authors

Publication date

Feb 2016

Summary

Country effects on outcomes for individuals are often analysed using multilevel (hierarchical) models applied to harmonized multi-country data sets such as ESS, EU-SILC, EVS, ISSP, and SHARE. We point out problems with the assessment of country effects that appear not to be widely appreciated, and develop our arguments using Monte Carlo simulation analysis of multilevel linear and logit models. With large sample sizes of individuals within each country but only a small number of countries, analysts can reliably estimate individual-level effects but estimates of parameters summarizing country effects are likely to be unreliable. Multilevel modelling methods are no panacea.

Published in

European Sociological Review

Volume and page numbers

32 , 3 -22

DOI

http://dx.doi.org/10.1093/esr/jcv059

ISSN

16

Notes

© The Author 2015. Published by Oxford University Press.; Open Access article; This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.


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  1. Regression analysis of country effects using multilevel data: a cautionary tale

    Mark L. Bryan and Stephen P. Jenkins

  2. Regression analysis of country effects using multilevel data: a cautionary tale

    Mark L. Bryan and Stephen P. Jenkins

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