Statistical conclusion validity: multiple inferences in rehabilitation research.
The problem of multiple statistical inferences and Type I error rates in rehabilitation research is examined. The Bonferroni method is the most commonly advocated procedure to control Type I error in clinical research. The traditional Bonferroni method is often overly conservative and results in a l...
| Publicado en: | American Journal of Physical Medicine & Rehabilitation Vol. 70; no. 6; pp. 317 - 323 |
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| Autor principal: | |
| Formato: | Journal Article |
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Lippincott Williams & Wilkins
1991 Dec
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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=107480910&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 107480910 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08949115 44N jtl: American Journal of Physical Medicine & Rehabilitation issn: 08949115 maglogo: N pubinfo: dt: 1991 Dec vid: 70 iid: 6 pid: 5086 pub: Lippincott Williams & Wilkins place: Baltimore, Maryland artinfo: ui: 107480910 107480910 1992135948 10.1097/00002060-199112000-00007 NLM1742003 107480910 ppf: 317 ppct: 6 formats: tig: atl: Statistical conclusion validity: multiple inferences in rehabilitation research. aug: au: Ottenbacher KJ affil: SUNY, Buffalo, 435 Kimball Tower, 3435 Main St, Buffalo, NY 14214 sug: subj: Statistics Research Methodology Validity Rehabilitation ab: The problem of multiple statistical inferences and Type I error rates in rehabilitation research is examined. The Bonferroni method is the most commonly advocated procedure to control Type I error in clinical research. The traditional Bonferroni method is often overly conservative and results in a loss of statistical power when more than a small number of comparisons are evaluated. Adjustments to the Bonferroni method designed to control or reduce the incidence of Type I errors and improve the statistical conclusion validity of rehabilitation research are presented. The adjusted or sharpened Bonferroni methods allow the researcher to control the incidence of Type I errors while maintaining statistical power. Adjustments to the Bonferroni method are simple to compute and applicable to a wide variety of statistical tests. The use of appropriate multiple comparison procedures will reduce the number of Type I errors and improve the statistical conclusion validity of rehabilitation research studies. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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