High-dimensional propensity score adjustment in studies of treatment effects using health care claims data

S Schneeweiss, JA Rassen, RJ Glynn, J Avorn… - …, 2009 - journals.lww.com
Background: Adjusting for large numbers of covariates ascertained from patients' health care
claims data may improve control of confounding, as these variables may collectively be …
被引用次数：1126 相关文章
[PDF] mcgill.ca

[PDF][PDF] High-dimensional propensity score adjustment in studies of treatment effects using health care claims data

S Schneeweiss, JA Rassen, RJ Glynn, J Avorn… - Epidemiology, 2009 - math.mcgill.ca
Background—Adjusting for large numbers of covariates ascertained from patients' health
care claims data may improve control of confounding, as these variables may collectively be …
[PDF] researchgate.net

[PDF][PDF] High-dimensional Propensity Score Adjustment in Studies of Treatment Effects Using Health Care Claims Data

S Schneeweiss, JA Rassen, RJ Glynn, J Avorn… - …, 2009 - researchgate.net
Background: Adjusting for large numbers of covariates ascertained from patients' health care
claims data may improve control of confounding, as these variables may collectively be …

High-dimensional Propensity Score Adjustment in Studies of Treatment Effects Using Health Care Claims Data

S Schneeweiss, JA Rassen, RJ Glynn, J Avorn… - Epidemiology, 2009 - JSTOR
Background: Adjusting for large numbers of covariates ascertained from patients' health care
claims data may improve control of confounding, as these variables may collectively be …

High-dimensional propensity score adjustment in studies of treatment effects using health care claims data.

S Schneeweiss, JA Rassen, RJ Glynn… - Epidemiology …, 2009 - europepmc.org
Background Adjusting for large numbers of covariates ascertained from patients' health care
claims data may improve control of confounding, as these variables may collectively be …

High-dimensional Propensity Score Adjustment in Studies of Treatment Effects Using Health Care Claims Data

S Schneeweiss, JA Rassen, RJ Glynn, J Avorn… - …, 2009 - journals.lww.com
Background: Adjusting for large numbers of covariates ascertained from patients' health care
claims data may improve control of confounding, as these variables may collectively be …

[引用][C] High-dimensional Propensity Score Adjustment in Studies of Treatment Effects Using Health Care Claims Data

S SCHNEEWEISS, JA RASSEN… - Epidemiology …, 2009 - pascal-francis.inist.fr
High-dimensional Propensity Score Adjustment in Studies of Treatment Effects Using
Health Care Claims Data CNRS Inist Pascal-Francis CNRS Pascal and Francis …

High-dimensional propensity score adjustment in studies of treatment effects using health care claims data

S Schneeweiss, JA Rassen… - Epidemiology …, 2009 - pubmed.ncbi.nlm.nih.gov
Background Adjusting for large numbers of covariates ascertained from patients' health care
claims data may improve control of confounding, as these variables may collectively be …
[HTML] nih.gov

[HTML][HTML] High-dimensional propensity score adjustment in studies of treatment effects using health care claims data

S Schneeweiss, JA Rassen, RJ Glynn… - Epidemiology …, 2009 - ncbi.nlm.nih.gov
Background Adjusting for large numbers of covariates ascertained from patients' health care
claims data may improve control of confounding, as these variables may collectively be …

[引用][C] High-dimensional Propensity Score Adjustment in Studies of Treatment Effects Using Health Care Claims Data

S Schneeweiss, JA Rassen, RJ Glynn, J Avorn… - Epidemiology, 2009 - cir.nii.ac.jp
High-dimensional Propensity Score Adjustment in Studies of Treatment Effects Using Health
Care Claims Data | CiNii Research CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ] 論文 …