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IRT and LC-IRT models for items with ordinal polytomous responses

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Genge E.
Econometrics. Ekonometria. Advances in Applied Data Analytics
|
2017
|
issue 4 (58)
62-76
EN
Item response theory (IRT) is a model-based theory in which the responses to test items depend on some person and item characteristics, according to specific probabilistic rela-tions. The simplest and most popular are dichotomous IRT models that specify a single (i.e. unidimensional) latent trait under the assumption of normal distribution. This article reviews the latent class ordinal polytomous item response models (LC-IRT) and presents the compari-son with the well-known traditional IRT models (based on the assumption of a normally dis-tributed latent trait). The main goal of the article is to compare the estimation results of differ-ent kinds of ordinal polytomous IRT models with continuous and discrete latent variable in measuring job satisfaction in Poland. We analyzed data collected as part of the International Social Survey Programme using the ltm and MultiLCIRT packages of R.
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