Statistical thinking in epidemiology:
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Boca Raton
CRC Press
2012
|
| Subjects: | |
| Online Access: | TUM01 Volltext |
| Item Description: | "A Chapman & Hall book." Includes bibliographical references (p. 189-202) and index "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"--Provided by publisher |
| Physical Description: | 1 Online-Ressource (xii, 219 p.) |
| ISBN: | 1420099922 9781420099928 |
Staff View
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Record in the Search Index
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| author | Tu, Yu-Kang |
| author_facet | Tu, Yu-Kang |
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| author_variant | y k t ykt |
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| dewey-full | 614.40727 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 614 - Forensic medicine; incidence of disease |
| dewey-raw | 614.40727 |
| dewey-search | 614.40727 |
| dewey-sort | 3614.40727 |
| dewey-tens | 610 - Medicine and health |
| discipline | Medizin |
| format | Electronic eBook |
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| id | DE-604.BV040474422 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T00:24:36Z |
| institution | BVB |
| isbn | 1420099922 9781420099928 |
| language | English |
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| physical | 1 Online-Ressource (xii, 219 p.) |
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| publishDate | 2012 |
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| publisher | CRC Press |
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| spelling | Tu, Yu-Kang Verfasser aut Statistical thinking in epidemiology Yu-Kang Tu ; Mark S. Gilthorpe Boca Raton CRC Press 2012 1 Online-Ressource (xii, 219 p.) txt rdacontent c rdamedia cr rdacarrier "A Chapman & Hall book." Includes bibliographical references (p. 189-202) and index "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"--Provided by publisher MEDICAL / Epidemiology bisacsh MEDICAL / Health Risk Assessment bisacsh Medizin Epidemiology / Statistical methods MEDICAL / Epidemiology / bisacsh MEDICAL / Health Risk Assessment / bisacsh Gilthorpe, Mark S. Sonstige oth Erscheint auch als Druck-Ausgabe, Hardcover 1-4200-9991-4 Erscheint auch als Druck-Ausgabe, Hardcover 978-1-4200-9991-1 http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=457316 Verlag Volltext |
| spellingShingle | Tu, Yu-Kang Statistical thinking in epidemiology MEDICAL / Epidemiology bisacsh MEDICAL / Health Risk Assessment bisacsh Medizin Epidemiology / Statistical methods MEDICAL / Epidemiology / bisacsh MEDICAL / Health Risk Assessment / bisacsh |
| title | Statistical thinking in epidemiology |
| title_auth | Statistical thinking in epidemiology |
| title_exact_search | Statistical thinking in epidemiology |
| title_full | Statistical thinking in epidemiology Yu-Kang Tu ; Mark S. Gilthorpe |
| title_fullStr | Statistical thinking in epidemiology Yu-Kang Tu ; Mark S. Gilthorpe |
| title_full_unstemmed | Statistical thinking in epidemiology Yu-Kang Tu ; Mark S. Gilthorpe |
| title_short | Statistical thinking in epidemiology |
| title_sort | statistical thinking in epidemiology |
| topic | MEDICAL / Epidemiology bisacsh MEDICAL / Health Risk Assessment bisacsh Medizin Epidemiology / Statistical methods MEDICAL / Epidemiology / bisacsh MEDICAL / Health Risk Assessment / bisacsh |
| topic_facet | MEDICAL / Epidemiology MEDICAL / Health Risk Assessment Medizin Epidemiology / Statistical methods MEDICAL / Epidemiology / bisacsh MEDICAL / Health Risk Assessment / bisacsh |
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