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dc.contributor.authorHartung, Joachim-
dc.contributor.authorKnapp, Guido-
dc.date.accessioned2009-02-02T10:45:39Z-
dc.date.available2009-02-02T10:45:39Z-
dc.date.issued2009-02-02T10:45:39Z-
dc.identifier.urihttp://hdl.handle.net/2003/26015-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-518-
dc.description.abstractIn all empirical or experimental sciences, it is a standard approach to present results, additionally to point estimates, in form of confidence intervals on the parameters of interest. The length of a confidence interval characterizes the accuracy of the whole findings. Consequently, confidence intervals should be constructed to hold a desired length. Basic ideas go back to Stein (1945) and Seelbinder (1953) who proposed a two-stage procedure for hypothesis testing about a normal mean. Tukey (1953) additionally considered the probability or power a confidence interval should possess to hold its length within a desired boundary. In this paper, an adaptive multi-stage approach is presented that can be considered as an extension of Stein's concept. Concrete rules for sample size updating are provided. Following an adaptive two-stage design of O'Brien and Fleming (1979) type, a real data example is worked out in detail.en
dc.language.isoen-
dc.subjectadaptive sample size planningen
dc.subjectgroup sequential trialen
dc.subjectlength of a confidence intervalen
dc.subjectmulti-stage confidence intervalen
dc.subjectpower of a confidence intervalen
dc.subject.ddc310-
dc.titleAdaptive confidence intervals of desired length and power for normal meansen
dc.typeText-
dc.type.publicationtypepreprint-
dcterms.accessRightsopen access-
Appears in Collections:Lehrstuhl Statistik mit Anwendungen im Bereich der Ingenieurwissenschaften

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