受测者潜在特质非正态分布时的IRT参数估计方法经典文献推荐之五

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Estimation of a Ramsay-Curve Item Response Theory Model by the Metropolis–Hastings Robbins–Monro Algorithm

Scott Monroe and Li Cai

Abstract
In Ramsay curve item response theory (RC-IRT) modeling, the shape of the latent trait distribution is estimated simultaneously with the item parameters. In its original implementation, RC-IRT is estimated via Bock and Aitkin’s EM algorithm, which yields maximum marginal likelihood estimates. This method, however, does not produce the parameter covariance matrix as an automatic byproduct on convergence. In turn, researchers are limited in when they can employ RC-IRT, as the covariance matrix is needed for many statistical inference procedures. The present research remedies this problem by estimating the RC-IRT model parameters by the Metropolis–Hastings Robbins–Monro (MH-RM) algorithm. An attractive feature of MH-RM is that the structure of the algorithm makes estimation of the covariance matrix convenient. Additionally, MH-RM is ideally suited for multidimensional IRT, whereas EM is limited by the ‘‘curse of dimensionality.’’ Based on the current research, when RC-IRTor similar IRT models are eventually generalized to include multiple latent dimensions, MHRM would appear to be the logical choice for estimation.

Keywords
Ramsay curve, item response theory, EM algorithm, MH-RM, density estimation

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关键词：非正态分布 经典文献 正态分布 参数估计 非正态

不错，先mark一下，到时候下载学习

好东西，测量越来越严谨了

shengzhouwang 发表于 2017-3-22 15:00
好东西，测量越来越严谨了

是的，我认为在使用模型之前最好能把模型做的完善一点。我上传的这几篇是从实际应用角度出发而进行的理论构建，从这里面可以看出，IRT仍需进一步完善。

Cai是这方面的大牛，flexMIRT软件的作者。Monroe和Cai的这篇研究非常具有参考价值。

thanks for your sharing, xie xie