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Understanding Clinical Data Analysis Learning Statistical Principles from Published Clinical Research 1st Editon 2018 Softbound at Meripustak

Understanding Clinical Data Analysis Learning Statistical Principles from Published Clinical Research 1st Editon 2018 Softbound by Ton J. Cleophas, Aeilko H. Zwinderman, Springer

Books from same Author: Ton J. Cleophas, Aeilko H. Zwinderman

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  • General Information  
    Author(s)Ton J. Cleophas, Aeilko H. Zwinderman
    PublisherSpringer
    Edition1st Edition
    ISBN9783319819174
    Pages234
    BindingSoftbound
    LanguageEnglish
    Publish YearJune 2018

    Description

    Springer Understanding Clinical Data Analysis Learning Statistical Principles from Published Clinical Research 1st Editon 2018 Softbound by Ton J. Cleophas, Aeilko H. Zwinderman

    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 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 past few years, the HOW-SO of current statistical tests has been made much more simple than it was in the past, thanks to the abundance of statistical software programs of an excellent quality. However, the WHY-SO may have been somewhat under-emphasized. For example, why do statistical tests constantly use unfamiliar terms, like probability distributions, hypothesis testing, randomness, normality, scientific rigor, and why are Gaussian curves so hard, and do they make non-mathematicians getting lost all the time? The book will cover the WHY-SOs. Preface.- Randomness.- Randomized and Observational Research.- Randomized Clinical Trials, Designs.- Randomized Clinical Trials, Analysis Sets, Statistical Analysis, Reporting Issues.- Discrete Data Analysis, Failure Time Data Analysis.- Quantitative Data Analysis.- Subgroup Analysis.- Interim Analysis.- Multiplicity Analysis.- Medical Statistics, a Discipline at the Interface of Biology and Mathematics.-Index.



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