Bayesian Methodology in Biostatistics
BST 249
Subject & Catalog Number
Jointly Offered with:
Faculty of Arts & Sciences as BIOSTAT 249
Course Information
Description
General principles of the Bayesian approach, prior distributions, hierarchical models and modeling techniques, approximate inference, Markov chain Monte Carlo methods, model assessment and comparison. Bayesian approaches to GLMMs, multiple testing, nonparametrics, clinical trails, survival analysis.
Course Note: lab or section times to be announced at first meeting; cross-listed: Harvard Chan Students must register for the Harvard Chan course.
School
Harvard Chan School
Credits
5
Cross Reg
Available for Harvard Cross Registration
Subject
Biostatistics
Grading Basis
HSPH Student Option (Audit, Ordinal, Pass/Fail)
Course Requirements
Prerequisites: BST231 and BST232 or instructor permission required
