Latent class models for testing monotonicity and invariant item ordering for polytomous items

被引:6
|
作者
Ligtvoet, Rudy [1 ]
Vermunt, Jeroen K. [2 ]
机构
[1] Univ Amsterdam, Dept Pedag & Educ Sci, NL-1018 VZ Amsterdam, Netherlands
[2] Tilburg Univ, Tilburg, Netherlands
关键词
BAYESIAN-ANALYSIS; RESPONSE THEORY; GIBBS SAMPLER; INFERENCE; LIKELIHOOD;
D O I
10.1111/j.2044-8317.2011.02019.x
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Two assumptions that are relevant to many applications using item response theory are the assumptions of monotonicity (M) and invariant item ordering (IIO). A latent class model is proposed for ordinal items with inequality constraints on the class-specific item means. This model is used as a tool for testing for violations of M and IIO. A Gibbs sampling scheme is used for estimating the model parameters. It is shown that the deviance information criterion can be used as an overall test of M and IIO, while posterior predictive checks can be used to test these assumptions at the item level. A real data application illustrates a model-fitting strategy for detecting items that violate M and IIO.
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页码:237 / 250
页数:14
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