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Analysis of a Complex Longitudinal Health-Related Quality of Life Data by a Mixed Logistic Model

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Abstract

We consider the context of a longitudinal study, where participants are interviewed about their health-related quality of life (HRQOL), at regular dates of visit, previously established. The interviews consist, to fulfill a questionnaire in which they are asked multiple choice questions, built in order to measure, at the time of the visit, the latent trait. We assume here unidimensionality of the latent trait. The issue of choosing a longitudinal model can be considered as one of the most important issue in latent regression models. In this work, we take the opportunity of a real longitudinal study of quality of life to present in detail the stages of the construction of a mixed logistic model. As, HRQOL is a latent variable, not directly observable, we use in this study, a measurement model from Rasch family to link the latent with item responses. We discuss the appropriate choice of interactions to include in the latent regression model.

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Correspondence to Mounir Mesbah .

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Mesbah, M. (2015). Analysis of a Complex Longitudinal Health-Related Quality of Life Data by a Mixed Logistic Model. In: Chen, Z., Liu, A., Qu, Y., Tang, L., Ting, N., Tsong, Y. (eds) Applied Statistics in Biomedicine and Clinical Trials Design. ICSA Book Series in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-12694-4_19

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