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Statistical Rethinking 2022 - Ordered Categories

Richard McElreath via YouTube

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Overview

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This lecture develops Bayesian models for ordered categorical outcomes, covering cumulative log-odds, ordered logit models, Dirichlet priors, sample bias, confounding, complex causal effects, and repeated observations.

Syllabus

Introduction
Trolley problems
Ordered categories
Cumulative log-odds
Ordered logit example
Sample bias and confounding
Intermission
Ordered predictors
Dirichlet priors
Big ordered logit model
Complex causal effects
Repeat observations and outlook

Taught by

Richard McElreath

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