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- W4380550798 abstract "This paper extends the generalized Hausman test to detect non-normality of the latent variable distribution in unidimensional IRT models for binary data. To build the test, we consider the estimator obtained from the two-parameter IRT model, that assumes normality of the latent variable, and the estimator obtained under a semi-nonparametric framework, that allows for a more flexible latent variable distribution. The behaviour of the test is evaluated through a simulation study. The results highlight the good performance of the test in terms of both Type I error rates and power with many items and large sample sizes." @default.
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- W4380550798 date "2023-01-01" @default.
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- W4380550798 title "Detecting Latent Variable Non-normality Through the Generalized Hausman Test" @default.
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- W4380550798 doi "https://doi.org/10.1007/978-3-031-27781-8_10" @default.
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