Key Statistical Concepts in Clinical Trials for Pharma [electronic resource] /by J. Rick Turner.
by Turner, J. Rick [author.]; SpringerLink (Online service).
Material type:
BookSeries: SpringerBriefs in Pharmaceutical Science & Drug Development: Publisher: New York, NY : Springer New York, 2012.Description: IX, 61p. 1 illus. online resource.ISBN: 9781461416623.Subject(s): Medicine | Pharmaceutical technology | Biomedicine | Biomedicine general | Pharmaceutical Sciences/TechnologyDDC classification: 610 Online resources: Click here to access online
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Springer eBooksSummary: This Brief discusses key statistical concepts that facilitate the inferential analysis of data collected from a group of individuals participating in a pharmaceutical clinical trial, the estimation of their clinical significance in the general population of individuals likely to be prescribed the drug if approved, and the related decision-making that occurs at both the public health level (by regulatory agencies when deciding whether or not to approve a new drug for marketing) and the individual patient level (by physicians and their patients when deciding whether or not the patient should be prescribed a drug that is on the market). These concepts include drug safety and efficacy, statistical significance, clinical significance, and benefit-risk balance.
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This Brief discusses key statistical concepts that facilitate the inferential analysis of data collected from a group of individuals participating in a pharmaceutical clinical trial, the estimation of their clinical significance in the general population of individuals likely to be prescribed the drug if approved, and the related decision-making that occurs at both the public health level (by regulatory agencies when deciding whether or not to approve a new drug for marketing) and the individual patient level (by physicians and their patients when deciding whether or not the patient should be prescribed a drug that is on the market). These concepts include drug safety and efficacy, statistical significance, clinical significance, and benefit-risk balance.
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