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Basic and Advanced Structural Equation Models for Medical and Behavioural Sciences introduces the Bayesian approach to SEMs, including the selection of prior distributions and data augmentation, and offers an overview of the subject’s recent advances. This book takes a Bayesian approach to SEMs allowing the use of prior information resulting in improved parameter estimates, latent variable estimates, and statistics for model comparison, as well as offering more reliable results for smaller samples.
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Basic and Advanced Structural Equation Models for Medical and Behavioural Sciences introduces the Bayesian approach to SEMs, including the selection of prior distributions and data augmentation, and offers an overview of the subject’s recent advances. This book takes a Bayesian approach to SEMs allowing the use of prior information resulting in improved parameter estimates, latent variable estimates, and statistics for model comparison, as well as offering more reliable results for smaller samples.