Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/111019
DC FieldValueLanguage
dc.contributor應數系
dc.creator姜志銘zh-tw
dc.creatorJiang, Thomas Jyh-Mingen-US
dc.date2017-06
dc.date.accessioned2017-07-12T07:13:43Z-
dc.date.available2017-07-12T07:13:43Z-
dc.date.issued2017-07-12T07:13:43Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/111019-
dc.description.abstractClinical trials are often costly, and time consuming. The ability to get new products into the market early is critical to the success of pharmaceutical and medical device companies. Most practitioners use Fisher`s exact tests to determine the required sample size for testing efficacy rates. We shall argue that when the sample size is not too small, normal approximation tests should be used instead of Fisher`s exact tests. Several different sets of hypotheses and their corresponding formulas to compute sample size for clinical trial based upon normal approximation test are given.
dc.format.extent160774 bytes-
dc.format.mimetypeapplication/pdf-
dc.relationBiomedical Statistics and Informatics, 2(3), 103-106
dc.subjectFisher’s Exact Test; Normal Approximation Test; Clinical Trial; Clinical Significance; Efficacy Rate
dc.titleOptimal Sample Size Determination for Medium or Large Clinical Study
dc.typearticle
dc.identifier.doi10.11648/j.bsi.20170203.14
dc.doi.urihttp://dx.doi.org/10.11648/j.bsi.20170203.14
item.grantfulltextrestricted-
item.cerifentitytypePublications-
item.openairetypearticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
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