Bayesian tests of measurement invariance
Bayesian tests of measurement invariance
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DOI：
10.1111/j.2044-8317.2012.02059.x
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发表时间：
2013-11-01
影响因子：
2.6
通讯作者：
Fox, J. P.
中科院分区：
文献类型：
--
作者：
Verhagen, A. J.;Fox, J. P.
随机项目效应模型提供了一个自然的框架，探索违反测量不变性，而不需要锚项目。在随机项目效应模型框架内，提出了贝叶斯检验（贝叶斯因子，偏差信息准则），使多个边际不变假设可以同时进行检验。测试的性能进行了评估与仿真研究表明，测试具有高功率和低I型错误率。从欧洲社会调查的数据被用来测试对移民项目的态度的测量不变性，并显示背景信息可以用来解释跨国项目功能的变化。
Random item effects models provide a natural framework for the exploration of violations of measurement invariance without the need for anchor items. Within the random item effects modelling framework, Bayesian tests (Bayes factor, deviance information criterion) are proposed which enable multiple marginal invariance hypotheses to be tested simultaneously. The performance of the tests is evaluated with a simulation study which shows that the tests have high power and low Type I error rate. Data from the European Social Survey are used to test for measurement invariance of attitude towards immigrant items and to show that background information can be used to explain cross-national variation in item functioning.