This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models. Following a gentle introduction to latent variable modeling, a wide range of estimation and prediction methods from biostatistics, psychometrics, econometrics, and statistics are explained and contrasted in a simple way. Exciting and realistic applications demonstrate how researchers can use latent variable modeling to solve concrete problems in areas as diverse as medicine, economics, and psychology. Many nonstandard response types are considered including ordinal, nominal, count, and survival data. Joint modeling of mixed responses such as survival and longitudinal data is also illustrated. Numerous displays, figures, and graphs make the text vivid and easy to read.

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