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161005 ||| eng |
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|a 9783319395869
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| 100 |
1 |
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|a Cleophas, Ton J.
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| 245 |
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|a Understanding Clinical Data Analysis
|h Elektronische Ressource
|b Learning Statistical Principles from Published Clinical Research
|c by Ton J. Cleophas, Aeilko H. Zwinderman
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| 250 |
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|a 1st ed. 2017
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2017, 2017
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| 300 |
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|a X, 234 p. 211 illus., 92 illus. in color
|b online resource
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| 505 |
0 |
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|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
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| 653 |
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|a Medical sciences
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| 653 |
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|a Health Sciences
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| 700 |
1 |
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|a Zwinderman, Aeilko H.
|e [author]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 028 |
5 |
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|a 10.1007/978-3-319-39586-9
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-319-39586-9?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 610
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| 520 |
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|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? Thebook will cover the WHY-SOs
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