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Introduction to Bayesian Inference

This chapter describes principles of Bayesian approaches to inference, with a focus on the mechanics of Bayesian inference. Along the way, several conceptual issues will be introduced or alluded to; we expand on these and a number of other conceptual issues in Chapter 3. To develop the mechanics of Bayesian inference, we first review frequentist approaches to inference, in particular maximum likelihood (ML) approaches, which then serves as a launching point for the description of Bayesian inference. Frequentist inference and estimation strategies have been the dominant approaches to psychometric modeling, mirroring their dominance in statistics generally in the past century. Provocatively, as discussed ...

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