Advanced Statistical Theory I-II

Course Description

This course focuses on drawing large sample inferences about "parameters" in statistical models. We develop asymptotic theory for maximum likelihood estimation, M-estimation, and generalized method of moment (GMM) estimation. Formal techniques for constructing estimators in semi-parametric models will be discussed. Particular attention will be paid to models for longitudinal and survival data. Guest lecturers will discuss special topics (e.g., targeted maximum likelihood, hypothesis testing, empirical likelihood). The course will involve rigorous mathematical arguments so that familiarity with concepts in advanced calculus, real analysis, and measure theory will be required.

Intended Audience

The course is designed for Biostatistics Ph.D. students in their 2nd year or beyond. Exceptions made with permission of the instructor.


Introduction to Probability Theory I-II (550.620-1), Introduction to Statistical Theory I-II (140.673-4), Real Analysis.

Recommended Textbooks

Lecture Notes