Literaturnachweis - Detailanzeige
| Autor/inn/en | Leite, Walter L.; Aydin, Burak; Gurel, Sungur |
|---|---|
| Titel | A Comparison of Propensity Score Weighting Methods for Evaluating the Effects of Programs with Multiple Versions |
| Quelle | In: Journal of Experimental Education, 87 (2019) 1, S.75-88 (14 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
| Zusatzinformation | ORCID (Leite, Walter L.) |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 0022-0973 |
| DOI | 10.1080/00220973.2017.1409179 |
| Schlagwörter | Probability; Weighted Scores; Monte Carlo Methods; Statistical Bias; Quasiexperimental Design; Error of Measurement; Computation; Statistical Analysis |
| Abstract | This Monte Carlo simulation study compares methods to estimate the effects of programs with multiple versions when assignment of individuals to program version is not random. These methods use generalized propensity scores, which are predicted probabilities of receiving a particular level of the treatment conditional on covariates, to remove selection bias. The results indicate that inverse probability of treatment weighting (IPTW) removes the most bias, followed by optimal full matching (OFM), and marginal mean weighting through stratification (MMWTS). The study also compared standard error estimation with Taylor series linearization, bootstrapping and the jackknife across propensity score methods. With IPTW, these standard error estimation methods performed adequately, but standard errors estimates were biased in most conditions with OFM and MMWTS. (As Provided). |
| Anmerkungen | Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2020/1/01 |
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