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BIOSTAT 901 - Advanced Inferential Techniques and Theory

Description
Stochastic processes, random walks, Markov chains, martingales, counting processes, weak convergence and basic empirical process theory and applications. Hilbert spaces for random vectors, semiparametric models, geometry of efficient score functions and efficient influence functions, construction of semiparametric efficient estimators. Applications include the restricted moment model and the proportional hazards model. The theory for M- and Z- estimators. Methods for dealing with missing data including imputation, inverse probability weighting (IPW) and the likelihood method, doubly robust IPW estimators. Instructor consent required. Instructor: Li
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Seminar
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Recent Semesters
Spring 2018
Offered
MW
Avg. Class Size
20
Avg. Sections
1