Testing for invariance of measurements across groups (such as countries or time points) is essential before meaningful comparisons may be conducted. However, when tested, invariance is often absent. As a result, comparisons across groups are potentially problematic and may be biased. In the current study, we propose utilizing a multilevel structural equation modeling (SEM) approach to provide a framework to explain item bias. We show how variation in a contextual variable may explain noninvariance. For the illustration of the method, we use data from the second round of the European Social Survey (ESS).
%0 Journal Article
%1 zora63109
%A Davidov, Eldad
%A Dülmer, Hermann
%A Schlüter, Elmar
%A Schmidt, Peter
%A Meuleman, Bart
%D 2012
%I Sage Publications
%J Journal of Cross-Cultural Psychology
%K (CFA) (SEM); ? European Social Survey; analysis and and?or comparisons configural, confirmatory countries equation factor invariance; metric, modeling multilevel over scalar structural time
%N 4
%P 558--575
%T Using a multilevel structural equation modeling approach to explain cross-cultural measurement noninvariance
%U http://www.zora.uzh.ch/63109/1/Davidov_Duelmer_Schlueter_Schmidt_Meuleman_JCCP.pdf
%V 43
%X Testing for invariance of measurements across groups (such as countries or time points) is essential before meaningful comparisons may be conducted. However, when tested, invariance is often absent. As a result, comparisons across groups are potentially problematic and may be biased. In the current study, we propose utilizing a multilevel structural equation modeling (SEM) approach to provide a framework to explain item bias. We show how variation in a contextual variable may explain noninvariance. For the illustration of the method, we use data from the second round of the European Social Survey (ESS).
@article{zora63109,
abstract = {Testing for invariance of measurements across groups (such as countries or time points) is essential before meaningful comparisons may be conducted. However, when tested, invariance is often absent. As a result, comparisons across groups are potentially problematic and may be biased. In the current study, we propose utilizing a multilevel structural equation modeling (SEM) approach to provide a framework to explain item bias. We show how variation in a contextual variable may explain noninvariance. For the illustration of the method, we use data from the second round of the European Social Survey (ESS). },
added-at = {2013-12-29T19:28:37.000+0100},
author = {Davidov, Eldad and D{\"u}lmer, Hermann and Schl{\"u}ter, Elmar and Schmidt, Peter and Meuleman, Bart},
biburl = {https://www.bibsonomy.org/bibtex/2a84afe4b1e98617d1e2ae9080163e437/stef1313},
interhash = {ac5ae7013fc5c19ad60e382225fd9983},
intrahash = {a84afe4b1e98617d1e2ae9080163e437},
journal = {Journal of Cross-Cultural Psychology},
keywords = {(CFA) (SEM); ? European Social Survey; analysis and and?or comparisons configural, confirmatory countries equation factor invariance; metric, modeling multilevel over scalar structural time},
note = {Copyright: Sage Publications},
number = 4,
pages = {558--575},
publisher = {Sage Publications},
timestamp = {2013-12-29T19:34:26.000+0100},
title = {Using a multilevel structural equation modeling approach to explain cross-cultural measurement noninvariance},
url = {http://www.zora.uzh.ch/63109/1/Davidov_Duelmer_Schlueter_Schmidt_Meuleman_JCCP.pdf},
volume = 43,
year = 2012
}