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Medical Care, 2003
Health services researchers are often interested in the effect of a treatment or a service in situations in which randomization is difficult or impossible. One useful alternative involves propensity score methods, a means for matching members of different groups based on a range of characteristics.
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Health services researchers are often interested in the effect of a treatment or a service in situations in which randomization is difficult or impossible. One useful alternative involves propensity score methods, a means for matching members of different groups based on a range of characteristics.
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Propensity Score Matching with Time‐Dependent Covariates
Biometrics, 2005SummaryIn observational studies with a time‐dependent treatment and time‐dependent covariates, it is desirable to balance the distribution of the covariates at every time point. A time‐dependent propensity score based on the Cox proportional hazards model is proposed and used in risk set matching. Matching on this propensity score is shown to achieve a
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Propensity Scores and Propensity Score Matching for Assessing Multiple Confounders
2012In the Chap. 23 methods for assessing confounders were reviewed. Propensity score are ideal for assessing confounding, particularly, if multiple confounders are in a study. E.g., age and cardiovascular risk factors may not be similarly distributed in two treatment groups of a parallel-group study. Propensity score matching is used to make observational
Ton J. Cleophas, Aeilko H. Zwinderman
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The American Statistician, 2008
Over the past 25 years, evaluators of social programs have searched for nonexperimental methods that can substitute effectively for experimental ones. Recently, the spotlight has focused on one method, propensity score matching (PSM), as the suggested approach for evaluating employment and education programs.
Peikes, Deborah N. +2 more
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Over the past 25 years, evaluators of social programs have searched for nonexperimental methods that can substitute effectively for experimental ones. Recently, the spotlight has focused on one method, propensity score matching (PSM), as the suggested approach for evaluating employment and education programs.
Peikes, Deborah N. +2 more
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Propensity Score Matching: Retrospective Randomization?
The Journal of Foot and Ankle Surgery, 2017Randomized controlled trials are viewed as the optimal study design. In this commentary, we explore the strength of this design and its complexity. We also discuss some situations in which these trials are not possible, or not ethical, or not economical.
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Propensity score matching [PDF]
The typical evaluation problem aims at quantifying the impact of a ÔtreatmentÕ (e.g. a training programme, a reform, or a medicine) on an outcome of interest (such as earnings, school attendance or illness indicators), where a group of units, the ÔtreatedÕ, receive the ÔtreatmentÕ, while a second group remains untreated.
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Matched or unmatched analyses with propensity‐score–matched data?
Statistics in Medicine, 2018Propensity‐score matching has been used widely in observational studies to balance confounders across treatment groups. However, whether matched‐pairs analyses should be used as a primary approach is still in debate. We compared the statistical power and type 1 error rate for four commonly used methods of analyzing propensity‐score–matched samples with
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[Propensity score matching in SPSS].
Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2016To realize propensity score matching in PS Matching module of SPSS and interpret the analysis results.The R software and plug-in that could link with the corresponding versions of SPSS and propensity score matching package were installed. A PS matching module was added in the SPSS interface, and its use was demonstrated with test data.Score estimation ...
Fuqiang, Huang +5 more
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