Zercher Florian, Schmidt Peter, Cieciuch Jan, Davidov Eldad
Department of Political Science, University of Giessen Giessen, Germany.
University Research Priority Program "Social Networks", University of Zürich Zürich, Switzerland ; Institute of Psychology, Cardinal Stefan Wyszyński University in Warsaw Warsaw, Poland.
Front Psychol. 2015 Jun 4;6:733. doi: 10.3389/fpsyg.2015.00733. eCollection 2015.
Over the last decades, large international datasets such as the European Social Survey (ESS), the European Value Study (EVS) and the World Value Survey (WVS) have been collected to compare value means over multiple time points and across many countries. Yet analyzing comparative survey data requires the fulfillment of specific assumptions, i.e., that these values are comparable over time and across countries. Given the large number of groups that can be compared in repeated cross-national datasets, establishing measurement invariance has been, however, considered unrealistic. Indeed, studies which did assess it often failed to establish higher levels of invariance such as scalar invariance. In this paper we first introduce the newly developed approximate approach based on Bayesian structural equation modeling (BSEM) to assess cross-group invariance over countries and time points and contrast the findings with the results from the traditional exact measurement invariance test. BSEM examines whether measurement parameters are approximately (rather than exactly) invariant. We apply BSEM to a subset of items measuring the universalism value from the Portrait Values Questionnaire (PVQ) in the ESS. The invariance of this value is tested simultaneously across 15 ESS countries over six ESS rounds with 173,071 respondents and 90 groups in total. Whereas, the use of the traditional approach only legitimates the comparison of latent means of 37 groups, the Bayesian procedure allows the latent mean comparison of 73 groups. Thus, our empirical application demonstrates for the first time the BSEM test procedure on a particularly large set of groups.
在过去几十年中,已经收集了诸如欧洲社会调查(ESS)、欧洲价值观研究(EVS)和世界价值观调查(WVS)等大型国际数据集,以比较多个时间点和许多国家的价值观均值。然而,分析比较调查数据需要满足特定假设,即这些价值观在不同时间和不同国家之间具有可比性。鉴于在重复的跨国数据集中可以比较的群体数量众多,然而,建立测量不变性被认为是不现实的。事实上,那些确实评估了测量不变性的研究往往未能建立更高水平的不变性,如标量不变性。在本文中,我们首先介绍基于贝叶斯结构方程建模(BSEM)新开发的近似方法,以评估不同国家和时间点的跨组不变性,并将结果与传统精确测量不变性检验的结果进行对比。BSEM检验测量参数是否近似(而非精确)不变。我们将BSEM应用于ESS中测量《肖像价值观问卷》(PVQ)中普遍主义价值观的项目子集。对该价值观的不变性在ESS的六个轮次中,同时在15个ESS国家进行了测试,共有173,071名受访者和90个组。而传统方法仅允许对37个组的潜在均值进行比较,贝叶斯程序则允许对73个组的潜在均值进行比较。因此,我们的实证应用首次在特别大量的组上展示了BSEM检验程序。