Simultaneous small sample inference based on profile likelihood [Elektronische Ressource] / Daniel Gerhard

Simultaneous small sample inferencebased on pro le likelihoodVon der Naturwissenschaftlichen Fakult atder Gottfried Wilhelm Leibniz Universit at Hannoverzur Erlangung des Grades einesDoktors der Gartenbauwissenschaften- Dr. rer. hort. -genehmigte DissertationvonDipl.-Ing. agr. Daniel Gerhardgeboren am 22.03.1979, in Castrop-Rauxel2010Referent: Prof. Dr. L. A. HothornKorreferent: Prof. Dr. D. HauschkeTag der Promotion: 09.06.2010AbstractGeneralized linear models allow the parameter estimation under assumption of a distribu-tion of the exponential family to summarize collected data. Based on the parameters ofthose models, tests can be conducted to reject a Null-hypothesis, or con dence intervalscan be calculated, giving an idea about the uncertainty of the parameter location with agiven error rate. If multiple parameters are of interest, multiplicity adjustment has to beperformed to control a global error rate for all tests or con dence intervals.In this thesis multiple tests and simultaneous con dence intervals are constructed basedon deviance pro les, which show directly the uncertainty about the location of a param-eter conditional on the given data. Statistics are obtained by minimizing the devianceconditional on a parameter of interest, allowing for a linear transformation by a pre-speci ed contrast matrix by considering additional constraints.