Matched or unmatched analyses with propensity-score-matched data?
Propensity-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 meth...
| Publicado en: | Statistics in Medicine Vol. 38; no. 2; pp. 289 - 301 |
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| Formato: | equations & formulas research tables/charts Journal Article |
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Wiley-Blackwell
Jan2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=133499365&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 133499365 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02776715 2DZ jtl: Statistics in Medicine issn: 02776715 maglogo: Y pubinfo: dt: Jan2019 vid: 38 iid: 2 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 133499365 133499365 NLM30276839 133499365 10.1002/sim.7976 NLM30276839 133499365 ppf: 289 ppct: 12 formats: tig: atl: Matched or unmatched analyses with propensity-score-matched data? aug: au: Wan, Fei affil: Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock Arkansas sug: subj: Data Analysis, Statistical Probability Models, Statistical Case Control Studies Linear Regression Treatment Outcomes Human ab: Propensity-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 continuous outcomes: (1) an unadjusted mixed-effects model, (2) an unadjusted generalized estimating method, (3) simple linear regression, and (4) multiple linear regression. Multiple linear regression had the highest statistical power among the four competing methods. We also found that the degree of intraclass correlation within matched pairs depends on the dissimilarity between the coefficient vectors of confounders in the outcome and treatment models. Multiple linear regression is superior to the unadjusted matched-pairs analyses for propensity-score-matched data. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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