Titlebook: Understanding Clinical Data Analysis; Learning Statistical Ton J. Cleophas,Aeilko H. Zwinderman Textbook 2017 Springer International Publis

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Subgroup Analysis,riables, the logistic regression models, and those for survival data, the Cox regression models, are only briefly mentioned here. This chapter was just an introduction of the principles of regression analysis. Regression analysis in clinical trials is, particularly, convenient to address questions l

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Interim Analysis,w many interim analyses do we need:.According to the American Food and Drug Administration’s Directives described in the International Conference of Harmonisation(ICH) Guidance, interim analysis must be distinguished from monitoring. The ICH paragraph E6 of the guidance says, that monitoring is for

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Multiplicity Analysis, and, consequently, producing multiple p-values. This phenomenon increases the risk of false positive results, because, if your chance of a false positive result is 5 % with one endpoint, it will be 10 % with two endpoints, etcetera. In practice, two possibilities will often be observed: (1) compari

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Textbook 2017e their clinical data, but still, wonder, after having done so, why procedures were performed the way they were. The book is also a must-read to those who tend to submerge in the flood of novel statistical methodologies, as communicated in current clinical reports, and scientific meetings..In the pa

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mples.Complementarily to real data examples, the book contin.This textbook consists of ten chapters, and is a must-read to all medical and health professionals, who already have basic knowledge of how to analyze their clinical data, but still, wonder, after having done so, why procedures were perfor

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