Stochastic EM for estimating the parameters of a multilevel IRT model

The British Journal of Mathematical and Statistical Psychology
J-P Fox


An item response theory (IRT) model is used as a measurement error model for the dependent variable of a multilevel model. The dependent variable is latent but can be measured indirectly by using tests or questionnaires. The advantage of using latent scores as dependent variables of a multilevel model is that it offers the possibility of modelling response variation and measurement error and separating the influence of item difficulty and ability level. The two-parameter normal ogive model is used for the IRT model. It is shown that the stochastic EM algorithm can be used to estimate the parameters which are close to the maximum likelihood estimates. This algorithm is easily implemented. The estimation procedure will be compared to an implementation of the Gibbs sampler in a Bayesian framework. Examples using real data are given.


May 6, 2008·Journal of Clinical Epidemiology·Paul K CraneGerald van Belle
Jun 23, 2005·The British Journal of Mathematical and Statistical Psychology·J-P Fox
Dec 5, 2018·The British Journal of Mathematical and Statistical Psychology·Siliang ZhangYang Liu
Jul 4, 2019·Statistics in Medicine·Gregory Camilli, Eugene Geis
Aug 3, 2013·Mathematical Biosciences and Engineering : MBE·Monika Joanna PiotrowskaJan Poleszczuk

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