Readings in Targeted Maximum Likelihood Estimation
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Abstract:
This is a compilation of current and past work on targeted maximum likelihood estimation. It features the original targeted maximum likelihood learning paper as well as chapters on super (machine) learning using cross validation, randomized controlled trials, realistic individualized treatment rules in observational studies, biomarker discovery, case-control studies, and time-to-event outcomes with censored data, among others. We hope this collection is helpful to the interested reader and stimulates additional research in this important area.
Subject Area:
General Biostatistics, Statistical Theory and Methods
Suggested Citation:
Mark J. van der Laan, Sherri Rose, and Susan Gruber, "Readings in Targeted Maximum Likelihood Estimation" (September 2009). U.C. Berkeley Division of Biostatistics Working Paper Series. Working Paper 254.
http://www.bepress.com/ucbbiostat/paper254