140.771.01
Advanced Statistical Theory I
Discontinued
 Location:
 East Baltimore
 Term:
 1st term
 Department:
 Biostatistics
 Credits:
 4 credits
 Academic Year:
 2022  2023
 Instruction Method:
 TBD
 Class Times:

 Tu Th, 1:30  2:50pm
 Auditors Allowed:
 Yes, with instructor consent
 Grading Restriction:
 Letter Grade or Pass/Fail
 Course Instructor:

 Daniel Scharfstein
 Contact:
 Daniel Scharfstein
 Frequency Schedule:
 Every Other Year
 Resources:
 Prerequisite:
Real Analysis, MeasureTheoretic Probability, Introduction to Statistical Theory III
 Description:

Focuses on drawing large sample inferences about "parameters" in statistical models. Develops asymptotic theory for maximum likelihood estimation, Mestimation, and generalized method of moment (GMM) estimation. Discusses formal techniques for constructing estimators in semiparametric models. Pays particular attention to models for longitudinal and survival data. Special topics presented by guest lecturers. Involves rigorous mathematical arguments so that familiarity with concepts in advanced calculus, real analysis, and measure theory will be required.
 Learning Objectives:

Upon successfully completing this course, students will be able to:
 Understand large sample theory underlying commonly used statistical procedures such as maximum likelihood, Mestimation, and GMMestimation.
 Understand the foundations of semiparametric inference.
 Understand the foundations of the counting process approach to survival analysis.
 Methods of Assessment:
Over two terms (140.771772): 4 collaborative homeworks (40%); 2 independent homeworks (40%); 1 final project (20%).
 Instructor Consent:
No consent required