Explore the complexities of missing data in statistical analysis through this comprehensive lecture from the Statistical Rethinking 2023 course. Delve into the representation of missing data in Directed Acyclic Graphs (DAGs), and gain insights into Bayesian imputation techniques. Learn how to handle incomplete datasets effectively, with the lecture divided into multiple parts for easier digestion. Enjoy brief musical interludes and a lighthearted moment featuring an icebear. Conclude with a summary and outlook on the implications of missing data in statistical modeling and analysis.
Statistical Rethinking 2023 - Missing Data
Overview
Syllabus
Introduction
Missing data in DAGs
Bayesian imputation part 1
Pause
Bayesian imputation part 2
Icebear fall down
Bayesian imputation part 3
Summary and outlook
Taught by
Richard McElreath
