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Multilevel models that combine individual and contextual factors are increasingly popular in comparative social science research; however, their application in country-comparative studies is often associated with several problems. First of all, most data-sets utilized for multilevel modeling include only a small number (N\textless30) of macro-level units, and therefore, the estimated models have a small number of degrees of freedom on the country level. If models are correctly specified paying regard to the small, level-2 N, only a few macro-level indicators can be controlled for. Furthermore, the introduction of random slopes and cross-level interaction effects is then hardly possible. Consequently, (1) these models are likely to suffer from omitted variable bias regarding the country-level estimators, and (2) the advantages of multilevel modeling cannot be fully exploited.
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EU-SILC-Bibliography
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The fixed effects approach as an alternative to multilevel analysis for cross-national analyses
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Bibsonomy
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In European Economic Review, 111, 85-97, 2019
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European Union Statistics on Income and Living Conditions (EU-SILC)
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2019
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SILC
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