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Propensity score matching [PDF]
, 2001 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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Integrative oncology: Addressing the global challenges of cancer prevention and treatment
Ca-A Cancer Journal for Clinicians, 2022Jun J Mao,, Msce +2 more
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Propensity Scores and Matching Methods
2018Many studies aim to estimate causal effects of risk factors, interventions, or programs, on outcomes of interest. While randomization is generally seen as the preferred design for estimating causal effects it is not always possible to randomize the “treatments” of interest, especially in the social sciences. Propensity scores are a useful tool that can
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Statistical Tools for Propensity Score Matching
Annals of Surgery, 2017Alain, Duhamel +3 more
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