12min chapter

Learning Bayesian Statistics cover image

#109 Prior Sensitivity Analysis, Overfitting & Model Selection, with Sonja Winter

Learning Bayesian Statistics

CHAPTER

Innovations in Bayesian Calibration

This chapter explores the intricacies and applications of Bayesian models, particularly in educational research and structural equation modeling. It emphasizes the efficiency of amortized Bayesian inference and addresses challenges related to missing data and small sample sizes. The speakers highlight the potential of Bayesian methods to provide deeper insights into complex data structures and inform policy decisions effectively.

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