A sample size planning approach that considers both statistical significance and clinical significance.
Background: The CONSORT statement requires clinical trials to report confidence intervals, which help to assess the precision and clinical importance of the treatment effect. Conventional sample size calculations for clinical trials, however, only consider issues of statistical significance (that is...
| Publicado en: | Trials Vol. 16; no. 1; pp. 213 - 214 |
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| Autores principales: | , |
| Formato: | Journal Article |
| Publicado: |
BioMed Central
2015
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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=109739079&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 109739079 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 17456215 38OC jtl: Trials issn: 17456215 maglogo: N pubinfo: dt: 2015 vid: 16 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 109739079 NLM25962998 2013021453 10.1186/s13063-015-0727-9 NLM25962998 PMC4455608 109739079 ppf: 213 ppct: 1 formats: tig: atl: A sample size planning approach that considers both statistical significance and clinical significance. aug: au: Jia, Bin Lynn, Henry S sug: ab: Background: The CONSORT statement requires clinical trials to report confidence intervals, which help to assess the precision and clinical importance of the treatment effect. Conventional sample size calculations for clinical trials, however, only consider issues of statistical significance (that is, significance level and power).Method: A more consistent approach is proposed whereby sample size planning also incorporates information on clinical significance as indicated by the boundaries of the confidence limits of the treatment effect.Results: The probabilities of declaring a "definitive-positive" or "definitive-negative" result (as defined by Guyatt et al., CMAJ 152(2):169-173, 1995) are controlled by calculating the sample size such that the lower confidence limit under H 1 and the upper confidence limit under H 0 are bounded by relevant cut-offs. Adjustments to the traditional sample size can be directly derived for the comparison of two normally distributed means in a test of nonequality, while simulations are used to estimate the sample size for evaluating the hazards ratio in a proportional-hazards model.Conclusions: This sample size planning approach allows for an assessment of the potential clinical importance and precision of the treatment effect in a clinical trial in addition to considerations of statistical power and type I error. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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