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Comparing the Two- and Three-Parameter Logistic Models via LikelihoodRatio Tests

机译:通过可能性比较二参数和三参数物流模型比率测试

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摘要

Selection of an appropriate item response model is critical in the measurement of latent examinee ability. The one-, two-, and three-parameter logistic (1PL, 2PL, and 3PL) models are nested, and as such can be compared using likelihood ratio (LR) tests. The null hypothesis in the LR test for selection among the 2PL and 3PL models sets the guessing parameters to their lower bound of 0. This violates one of the assumptions of the LR test and renders the usual χ2 reference distribution inappropriate for the comparison. A review of the current literature revealed that this problem is not well understood in the educational measurement field. Ignoring this issue can lead to selection of an overly simplified model, with implications for the ability estimates. In this article, the use of the LR test for item response model selection is investigated, with the goal of providing practitioners with an appropriate method of selecting the most parsimonious model. The results of simulation studies indicate the nature of the problem, with inaccurate Type I error rates for cases where the inappropriate null distribution was used. An analysis of data from a statewide mathematics test showed differences pertinent to subsequent analyses.
机译:在评估潜在应试者能力时,选择合适的项目反应模型至关重要。一参数,二参数和三参数逻辑模型(1PL,2PL和3PL)是嵌套的,因此可以使用似然比(LR)测试进行比较。在LR测试中选择2PL和3PL模型的原假设将猜测参数设置为其下界0。这违反了LR测试的假设之一,并提供了通常的χ 2 参考分布不适合比较。对现有文献的回顾表明,这个问题在教育测量领域还没有得到很好的理解。忽略此问题可能会导致选择过于简化的模型,从而影响能力估计。在本文中,研究了将LR检验用于项目响应模型选择的目的,目的是为从业人员提供选择最简约模型的适当方法。仿真研究的结果表明了问题的性质,对于使用不适当的零分布的情况,I类错误率不正确。对全州数学测试数据的分析表明,与后续分析有关的差异。

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