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Understanding clinical data analysis...

Cleophas, Ton J.

Understanding clinical data analysislearning statistical principles from published clinical research /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Understanding clinical data analysisby Ton J. Cleophas, Aeilko H. Zwinderman.
Reminder of title:	learning statistical principles from published clinical research /
Author:	Cleophas, Ton J.
other author:	Zwinderman, Aeilko H.
Published:	Cham :Springer International Publishing :2017.
Description:	x, 234 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Clinical medicineResearch
Online resource:	http://dx.doi.org/10.1007/978-3-319-39586-9
ISBN:	9783319395869$q(electronic bk.)

Understanding clinical data analysislearning statistical principles from published clinical research /
Cleophas, Ton J.

Understanding clinical data analysislearning statistical principles from published clinical research /[electronic resource] :by Ton J. Cleophas, Aeilko H. Zwinderman. - Cham :Springer International Publishing :2017. - x, 234 p. :ill. (some col.), digital ;24 cm.

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.

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.

ISBN: 9783319395869$q(electronic bk.)

Standard No.: 10.1007/978-3-319-39586-9doiSubjects--Topical Terms:

490519
Clinical medicine
--Research

LC Class. No.: R853.S7

Dewey Class. No.: 610.724

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245 1 0 $a Understanding clinical data analysis $h [electronic resource] : $b learning statistical principles from published clinical research / $c by Ton J. Cleophas, Aeilko H. Zwinderman.
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505 0 $a 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.
520 $a 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.
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