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Statistical Analysis of Clinical Data on a Pocket Calculator

Statistics on a Pocket Calculator

Author(s):
Publisher:

Springer

Pages: 58
Further Actions:

Recommend to library

AVAILABLE FORMATS

Hardcover - 9789400712102

06 May 2011

$84.99

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Ebook - 9789400712119

26 April 2011

$64.99

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The core principles of statistical analysis are too easily forgotten in today’s world of powerful computers and time-saving algorithms. This step-by-step primer takes researchers who lack the confidence to conduct their own...

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The core principles of statistical analysis are too easily forgotten in today’s world of powerful computers and time-saving algorithms. This step-by-step primer takes researchers who lack the confidence to conduct their own analyses right back to basics, allowing them to scrutinize their own data through a series of rapidly executed reckonings on a simple pocket calculator. A range of easily navigable tutorials facilitate the reader’s assimilation of the techniques, while a separate chapter on next generation Flash prepares them for future developments in the field. This practical volume also contains tips on how to deny hackers access to Flash internet sites. An ideal companion to the author’s co-authored works on statistical analysis for Springer such as Statistics Applied to Clinical Trials, this monograph will help researchers understand the processes involved in interpreting clinical data, as well as being a necessary prerequisite to mastering more advanced statistical techniques.

 The principles of statistical analysis are easily forgotten in today’s world of time-saving algorithms. This step-by-step primer takes researchers back to basics, enabling them to examine their own data through a series of sums on a simple pocket calculator.

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It addresses those who wish to understand statistics but have no time for complex mathematics.

With less than 100 pages the book yet covers all relevant pocket calculator statistical methods.

An alternative book with similar content is not available on the market.

Similar contents may be covered in textbooks in a scattered way, but the current text highlights the essentials and leaves out the less important aspects.

It is a primer for the book "SPSS for Starters".

Chapter 1: Introduction. Chapter 2: Standard deviation. Chapter 3: T-tests. Chapter 4: Non-parametric tests. Chapter 5: Confidence interval. Chapter 6: Equivalence testing. Chapter 7: Power-equations. Chapter 8: Sample size. hapter 9: Non-inferiority testing. Chapter 10: Z-test for cross-tabs. Chapter 11: Chi-square test for cross-tabs. Chapter 13: Odds ratios. Chapter 12: Log likelihood ratio tests. Chapter 14: McNemar’s t-test. Chapter 15: Bonferroni t-test. Chapter 16: Variability analysis. Chapter 17: Confounding. Chapter 18: Interaction. Chapter 19: Duplicate standard deviation for reliability assessment of continuous data. Chapter 20: Kappas for reliability assessment of binary data. Final remarks. Index                                   

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Professor Zwinderman is past-president of the International Society of Biostatistics (2012-2015), and Professor Cleophas is past-president of the American College of Angiology (2000-2002). From their expertise they should be able to make adequate selections of modern methods for clinical data analysis for the benefit of physicians, students, and investigators. 

The authors have been working and publishing together for 17 years, and their research can be characterized as a continued effort to demonstrate that clinical data analysis is not mathematics but rather a discipline at the interface of biology and mathematics.

The authors as professors and teachers in statistics at universities in The Netherlands and...

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Professor Zwinderman is past-president of the International Society of Biostatistics (2012-2015), and Professor Cleophas is past-president of the American College of Angiology (2000-2002). From their expertise they should be able to make adequate selections of modern methods for clinical data analysis for the benefit of physicians, students, and investigators. 

The authors have been working and publishing together for 17 years, and their research can be characterized as a continued effort to demonstrate that clinical data analysis is not mathematics but rather a discipline at the interface of biology and mathematics.

The authors as professors and teachers in statistics at universities in The Netherlands and France for the most part of their lives, are convinced that the scientific method of statistical reasoning and hypothesis testing is little used by physicians and other health workers, and they hope that the current production will help them find the appropriate ways for answering their scientific questions.   

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