Latent Variable Models of Categorical Responses in the Bayesian and Frequentist Frameworks
Tarek Farouni · OhioLink ETD Center (Ohio Library and Information Network) · 2014
The thesis consists of two self-contained manuscripts.The first manuscript presents a Bayesian multilevel formulation of a cross-classified latent variable model for categorical responses.In the manuscript, we discuss the issue of model non-identifiability and how parameter constraints in the form of item-level regression covariates can aid in model identification.We use the latent regression identification strategy to fit one of two models that we propose to examine the latent structure of emotional distress regarding aspects of anxiety and depression.The models are fit to an empirical dataset consisting of item responses on the Patient-Reported Outcomes Measurement Information System (PROMIS ) profile of emo-I would like to thank my advisor Dr. Paul De Boeck for his unswerving commitment and support over the past year, and most importantly, for his valuable guidance, from initially proposing the research topics, to finally making sure that the thesis is ready after critically reading and providing feedback multiple times throughout the writing process.I would also like to thank the rest of my thesis committee,