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Covariate Selection in High-Dimensional Propensity Score Analyses of Treatment Effects in Small Samples

To reduce bias by residual confounding in nonrandomized database studies, the high-dimensional propensity score (hd-PS) algorithm selects and adjusts for previously unmeasured confounders. The authors evaluated whether hd-PS maintains its capabilities in small cohorts that have few exposed patients...

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Autori principali: Rassen, Jeremy A., Glynn, Robert J., Brookhart, M. Alan, Schneeweiss, Sebastian
Natura: Artigo
Lingua:Inglês
Pubblicazione: Oxford University Press 2011
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Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC3145392/
https://ncbi.nlm.nih.gov/pubmed/21602301
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/aje/kwr001
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