BITESIZE | Why Your Models Might Be Wrong & How to Fix it, with Sean Pinkney & Adrian Seyboldt
Learning Bayesian Statistics
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Navigating Hierarchical Models with Zero-Sum Constraints
This chapter explores the intricacies of hierarchical modeling with an emphasis on zero-sum constraints in random and fixed effects. It highlights the effect of normal distribution assumptions on parameter estimation and emphasizes how zero-sum constraints can enhance accuracy and sampling efficiency.
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