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Explaining Measurement Nonequivalence Using Multilevel Structural Equation Modeling: The Case of Attitudes Toward Citizenship Rights


Davidov, Eldad; Dülmer, Hermann; Cieciuch, Jan; Kuntz, Anabel; Seddig, Daniel; Schmidt, Peter (2016). Explaining Measurement Nonequivalence Using Multilevel Structural Equation Modeling: The Case of Attitudes Toward Citizenship Rights. Sociological Methods & Research:Epub ahead of print.

Abstract

It is necessary to test for equivalence of measurements across groups to guarantee that comparisons of regression coefficients or mean scores of a latent factor are meaningful. Unfortunately, when tested, many scales display non-equivalence. Several researchers have suggested that non-equivalence may be used as a useful source of information as to why equivalence is biased and proposed employing a multilevel structural equation modeling (MLSEM) approach to explain why equivalence is not given. This method can consider a latent between-level factor and/or single contextual variables and use them to explain items’ non-equivalence. In the current study we show that this method may also be useful for social science studies in general and for survey research and sociological comparative studies in particular when one fails to establish cross-group equivalence. We utilize data from the International Social Survey Program (ISSP) national identity module (2003) to test for the cross-country equivalence of a scale measuring attitudes toward granting citizenship rights to immigrants. As expected, the scale fails to achieve scalar equivalence. However, we explain a significant part of the most non-equivalent intercept by a latent between-level factor and one contextual variable, namely, the percentage of foreigners in the country relying on group threat theory. We show that the method does not necessarily rectify non-equivalence but it can help to explain why it is absent.

Abstract

It is necessary to test for equivalence of measurements across groups to guarantee that comparisons of regression coefficients or mean scores of a latent factor are meaningful. Unfortunately, when tested, many scales display non-equivalence. Several researchers have suggested that non-equivalence may be used as a useful source of information as to why equivalence is biased and proposed employing a multilevel structural equation modeling (MLSEM) approach to explain why equivalence is not given. This method can consider a latent between-level factor and/or single contextual variables and use them to explain items’ non-equivalence. In the current study we show that this method may also be useful for social science studies in general and for survey research and sociological comparative studies in particular when one fails to establish cross-group equivalence. We utilize data from the International Social Survey Program (ISSP) national identity module (2003) to test for the cross-country equivalence of a scale measuring attitudes toward granting citizenship rights to immigrants. As expected, the scale fails to achieve scalar equivalence. However, we explain a significant part of the most non-equivalent intercept by a latent between-level factor and one contextual variable, namely, the percentage of foreigners in the country relying on group threat theory. We show that the method does not necessarily rectify non-equivalence but it can help to explain why it is absent.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Sociology
08 University Research Priority Programs > Social Networks
Dewey Decimal Classification:300 Social sciences, sociology & anthropology
Uncontrolled Keywords:measurement equivalence; multilevel structural equation modeling; ISSP; percentage of foreigners in the country; attitudes toward granting citizenship rights to immigrants
Language:English
Date:2016
Deposited On:28 Oct 2016 06:29
Last Modified:28 Oct 2016 06:35
Publisher:Sage Publications Ltd.
ISSN:0049-1241
Funders:UFSP Soziale Netzwerke
Publisher DOI:https://doi.org/10.1177/0049124116672678

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