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Statistical Thinking in Epidemiology

By (author) Yu-Kang Tu, By (author) Mark Gilthorpe

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normal price: R 2 948.95

Price: R 2 801.95


| book description |

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.

| product details |



Normally shipped | This title will take longer to obtain, and should be delivered in 6-8 weeks
Publisher | Taylor & Francis Ltd
Published date | 19 Sep 2019
Language |
Format | Paperback / softback
Pages | 232
Dimensions | 234 x 156 x 0mm (L x W x H)
Weight | 453g
ISBN | 978-0-3673-8255-1
Readership Age |
BISAC | mathematics / probability & statistics / general


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Normally shipped | Available from overseas. Usually dispatched in 14 days
Readership Age |
Normal Price | R 3 460.95
Price | R 3 287.95 | on special |



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