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Activity Number: 59
Type: Topic Contributed
Date/Time: Sunday, July 31, 2016 : 4:00 PM to 5:50 PM
Sponsor: Health Policy Statistics Section
Abstract #320326
Title: Maximizing the Information Content of a Balanced Matched Sample
Author(s): Jose Zubizarreta* and Cinar Kilcioglu
Companies: Columbia University and Columbia University
Keywords: Causal inference ; Matched sampling ; Observational studies ; Propensity score

We propose a general framework for matching in observational studies and specific matching methods within this framework that simultaneously achieve three goals: (i) maximize the information content of a matched sample; (ii) form the matches using a flexible matching structure (such as a one-to-many/many-to-one structure); and (iii) directly attain covariate balance as specified -before matching- by the investigator.

Authors who are presenting talks have a * after their name.

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