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Statistical thinking in epidemiology
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| 概要 | "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 s...tatistical 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"--Provided by publisher.続きを見る |
| 目次 | Vector geometry of linear models for epidemiologists Path diagrams and directed acyclic graphs Mathematical coupling and regression to the mean in the relation between change and initial value Analysis of change in pre-/post-test studies Collinearity and multicollinearity Is reverse paradox a paradox? Testing statistical interaction Finding growth trajectories in lifecourse research Partial least squares regression for lifecourse research. |
| アクセス注記 | Taylor & Francis eBooks DRM Free Collection トライアル中(2023/3/31まで利用可能) 【Trial】This title is available until March 31, 2023. |
| 本文を見る | Taylor & Francis eBooks DRM Free Collection: 2011 |
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| 登録日 | 2023.01.20 |
| 更新日 | 2023.01.20 |