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Title: Comparison between likelihood-based methods of factor models for ordinal data Authors:  Silvia Cagnone - University of Bologna (Italy) [presenting]
Silvia Bianconcini - University of Bologna (Italy)
Abstract: Latent variable models represent a useful tool in different fields of research in which the constructs of interest are not directly observable. In presence of many latent variables/random effects, problems related to the integration of the likelihood function can arise since analytical solutions do not exist. In literature, different solutions have been proposed to overcome these problems. Among these, the composite likelihoods method and more recently the dimension-wise method have been shown to produce estimators with desirable properties. We compare the performance of the two methods in the case of longitudinal ordinal data.