Francesco, Bartolucci and Silvia, Bacci and Claudia, Pigini (2015): A misspecification test for finitemixture logistic models for clustered binary and ordered responses.
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Abstract
An alternative to using normally distributed random effects in modeling clustered binary and ordered responses is based on using a finitemixture. This approach gives rise to a flexible class of generalized linear mixed models for item responses, multilevel data, and longitudinal data. A test of misspecification for these finitemixture models is proposed which is based on the comparison between the Marginal and the Conditional Maximum Likelihood estimates of the fixed effects as in the Hausman’s test. The asymptotic distribution of the test statistic is derived; it is of chisquared type with a number of degrees of freedom equal to the number of covariates that vary within the cluster. It turns out that the test is simple to perform and may also be used to select the number of components of the finitemixture, when this number is unknown. The approach is illustrated by a series of simulations and three empirical examples covering the main fields of application.
Item Type:  MPRA Paper 

Original Title:  A misspecification test for finitemixture logistic models for clustered binary and ordered responses 
Language:  English 
Keywords:  Generalized Linear Mixed Models, Hausman Test, Item Response Theory, Latent Class model, Longitudinal data, Multilevel data 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C12  Hypothesis Testing: General C  Mathematical and Quantitative Methods > C2  Single Equation Models ; Single Variables > C23  Panel Data Models ; Spatiotemporal Models C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C52  Model Evaluation, Validation, and Selection 
Item ID:  64220 
Depositing User:  Dr Claudia Pigini 
Date Deposited:  08 May 2015 15:50 
Last Modified:  02 Oct 2019 13:38 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/64220 
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