Alternative approaches for confounding adjustment in observational studies using weighting based on the propensity score: a primer for practitioners

被引：413

作者：

Desai, Rishi J. ^{[1
,2
]}

Franklin, Jessica M. ^{[1
,2
]}

机构：

[1] Brigham & Womens Hosp, Div Pharmacoepidemiol & Pharmacoecon, 1620 Tremont St, Boston, MA 02120 USA

[2] Harvard Med Sch, 1620 Tremont St, Boston, MA 02120 USA

来源：

BMJ-BRITISH MEDICAL JOURNAL | 2019年 / 367卷

关键词：

CAUSAL INFERENCE; LOGISTIC-REGRESSION; PERFORMANCE; SELECTION; SETTINGS; EXPOSURE; OUTCOMES; COMPARE; MODELS; RISK;

D O I：

10.1136/bmj.l5657

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

This report aims to provide methodological guidance to help practitioners select the most appropriate weighting method based on propensity scores for their analysis out of many available options (eg, inverse probability treatment weights, standardised mortality ratio weights, fine stratification weights, overlap weights, and matching weights), and outlines recommendations for transparent reporting of studies using weighting based on the propensity scores.

引用

页数：10

共 24 条

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EPIDEMIOLOGY, 2017, 28 (02) : 249 - 257
[8] The Association Between Congestive Heart Failure and One-Year Mortality After Surgery in Singaporean Adults: A Secondary Retrospective Cohort Study Using Propensity-Score Matching, Propensity Adjustment, and Propensity-Based Weighting
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[9] Confounder-adjusted estimates of the risk difference using propensity score-based weighting
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[10] Studies with Many Covariates and Few Outcomes Selecting Covariates and Implementing Propensity-Score-Based Confounding Adjustments
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