Statistical Thinking in Epidemiology

Chapman and Hall/CRC
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9780367382551
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ISBN13:
9780367382551
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While biomedical researchers may be able to follow instructions in the manuals accompanying the statistical software packages, they do not always have sufficient knowledge to choose the appropriate statistical methods and correctly interpret their results. Statistical Thinking in Epidemiology examines common methodological and statistical problems in the use of correlation and regression in medical and epidemiological research: mathematical coupling, regression to the mean, collinearity, the reversal paradox, and statistical interaction. Statistical Thinking in Epidemiology is about thinking statistically when looking at problems in epidemiology. The authors focus on several methods and look at them in detail: specific examples in epidemiology illustrate how different model specifications can imply different causal relationships amongst variables, and model interpretation is undertaken with appropriate consideration of the context of implicit or explicit causal relationships. This book is intended for applied statisticians and epidemiologists, but can also be very useful for clinical and applied health researchers who want to have a better understanding of statistical thinking. Throughout the book, statistical software packages R and Stata are used for general statistical modeling, and Amos and Mplus are used for structural equation modeling.
  • | Author: Yu-Kang Tu, Mark Gilthorpe
  • | Publisher: Chapman And Hall/Crc
  • | Publication Date: Sep 19, 2019
  • | Number of Pages: 232 pages
  • | Language: English
  • | Binding: Paperback
  • | ISBN-10: 0367382555
  • | ISBN-13: 9780367382551
Author:
Yu-Kang Tu, Mark Gilthorpe
Publisher:
Chapman And Hall/Crc
Publication Date:
Sep 19, 2019
Number of pages:
232 pages
Language:
English
Binding:
Paperback
ISBN-10:
0367382555
ISBN-13:
9780367382551