Biostatistical Design and Analyses of Long-Term Animal Studies Simulating Human Postmenopausal Osteoporosis

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dc.identifier.uri http://dx.doi.org/10.15488/2986
dc.identifier.uri http://www.repo.uni-hannover.de/handle/123456789/3016
dc.contributor.author Hothorn, Ludwig A.
dc.contributor.author Bauss, Frieder
dc.date.accessioned 2018-02-28T13:27:46Z
dc.date.available 2018-02-28T13:27:46Z
dc.date.issued 2004
dc.identifier.citation Hothorn, L.A.; Bauss, F.: Biostatistical Design and Analyses of Long-Term Animal Studies Simulating Human Postmenopausal Osteoporosis. In: Therapeutic Innovation & Regulatory Science 38 (2004), Nr. 1, S. 47-56. DOI: https://doi.org/10.1177/009286150403800107
dc.description.abstract Using three well-designed experimental studies as illustration, we demonstrate that the biostatistical design and analysis of long-term animal studies simulating human osteoporosis should be analogous to the design and analysis of randomized clinical trials. This principal is in accordance with the recommendations from the International Conference on Harmonisation guidelines concerning statistical principles in clinical trials (1). An important element of biostatistical study design is sample size. The three studies that are described herein used an a-priori sample size estimation for the one-way layout that included controls and several treatment and dose groups. In these k-sample designs, with at least one control group, both the multiple comparison procedure and trend tests within procedures for identification of the minimal-effective dose are recommended. Although p-values in pharmacology are quite common, confidence intervals should be used according to their interpretation for both statistical significance and clinical relevance. The use of one-sided confidence intervals for both the difference and the ratio to control for proving either superiority or at least noninferiority is demonstrated by real data examples. Relevant and relatively straightforward software is available for biostatistical analysis and can also be used to aid design. In summary, referring to published, well-designed experimental studies can help to assist with ensuring the quality of future investigations. © 2004, Drug Information Association. All rights reserved. eng
dc.language.iso eng
dc.publisher London : SAGE Publications Ltd.
dc.relation.ispartofseries Therapeutic Innovation & Regulatory Science 38 (2004), Nr. 1
dc.rights Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. Dieser Beitrag ist aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.
dc.subject comparison eng
dc.subject Confidence interval for the ratio eng
dc.subject Ibanthonate eng
dc.subject Many-to-one eng
dc.subject Minimum-effective dose eng
dc.subject Osteoporosis eng
dc.subject Pharmacological study eng
dc.subject.ddc 610 | Medizin, Gesundheit ger
dc.title Biostatistical Design and Analyses of Long-Term Animal Studies Simulating Human Postmenopausal Osteoporosis eng
dc.type article
dc.type Text
dc.relation.issn 2168-4790
dc.relation.doi https://doi.org/10.1177/009286150403800107
dc.bibliographicCitation.issue 1
dc.bibliographicCitation.volume 38
dc.bibliographicCitation.firstPage 47
dc.bibliographicCitation.lastPage 56
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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