Variable selection and raking in propensity scoring | Zendy

Judkins David R. | Zendy; Morganstein David | Zendy; Zador Paul | Zendy; Piesse Andrea | Zendy; Barrett Brandon | Zendy; Mukhopadhyay Pushpal | Zendy

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Variable selection and raking in propensity scoring

Author(s) -

Judkins David R.,

Morganstein David,

Zador Paul,

Piesse Andrea,

Barrett Brandon,

Mukhopadhyay Pushpal

Publication year - 2006

Publication title -

statistics in medicine

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.996

H-Index - 183

eISSN - 1097-0258

pISSN - 0277-6715

DOI - 10.1002/sim.2591

Subject(s) - covariate , propensity score matching , computer science , context (archaeology) , selection (genetic algorithm) , econometrics , statistics , measure (data warehouse) , machine learning , mathematics , data mining , biology , paleontology

This paper discusses some practical issues in applying propensity scoring in the context of endpoint analysis in a pre‐/posttest longitudinal design with an ordinal measure of treatment intensity and a high‐dimensional potential covariate space: how many covariates to include in propensity models; how to evaluate the adequacy of tentative propensity models; and how to tailor models to provide hypercontrol on a limited subset of covariates. These issues arose in the evaluation of a health communication program. Copyright © 2006 John Wiley & Sons, Ltd.

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