Common Statistical Methods for Clinical Research with SAS Examples, Second Edition - Softcover

Walker Ph.D., Glenn A.

 
9781590470404: Common Statistical Methods for Clinical Research with SAS Examples, Second Edition

Inhaltsangabe

Common Statistical Methods for Clinical Research with SAS Examples, Second Edition, written by Glenn Walker, provides clinical researchers with an invaluable aid for understanding the statistical methods cited most frequently in clinical protocols, statistical analysis plans, clinical and statistical reports, and medical journals. The text is written in a way that takes the non-statistician through each test using examples, yet substantive details are presented that benefit even the most experienced data analyst. Introductory chapters provide elementary statistical concepts as applied to clinical trials and an overview of statistical inference, including discussions about power, calculating sample size, p-values, and the logic behind hypothesis testing. The statistical methods discussed here represent a composite of methods most commonly used in the analysis of clinical research data. Numerous examples taken from clinical research show how to calculate statistical data both manually and using SAS. This revised edition includes sections about crossover designs and multiple comparison methods, a discussion of interim analyses, 50% more examples, and reader exercises. Extensions of methods previously presented only in their most elementary form are shown in new examples.

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Über die Autorin bzw. den Autor

Glenn A. Walker has been providing statistical consulting services to the biopharmaceutical industry since 1977. He received his Ph.D. in statistics from the University of Florida where, as a graduate student, he taught courses in statistics and how to use SAS software. He has worked as a consultant to numerous pharmaceutical and biotechnology companies in study design, data analysis, and statistical programming in the field of clinical trials. In this book, Glenn draws on his extensive experience with the statistical handling of data from various types of medical conditions and treatments to illustrate commonly used statistical methods.

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