Statistics for epidemiology
Develops the techniques for analyzing simple risk factors and disease data, with step-by-step extensions that include the use of binary regression. It covers the logistic regression model in detail and contrasts it with the Cox model for time-to-incidence data. The author uses a few simple case studies to guide readers from elementary analyses to more complex regression modeling. Following these examples through several chapters makes it easy to compare the interpretations that emerge from vary…
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- Full title :Statistics for epidemiology / by Nicholas P. Jewell.
Summary
Develops the techniques for analyzing simple risk factors and disease data, with step-by-step extensions that include the use of binary regression. It covers the logistic regression model in detail and contrasts it with the Cox model for time-to-incidence data. The author uses a few simple case studies to guide readers from elementary analyses to more complex regression modeling. Following these examples through several chapters makes it easy to compare the interpretations that emerge from varying approaches.
Read More ↓Edition Statements
- Publication Date:©2004.
Publication Statements
- Publisher(s):Chapman & Hall/CRC
- Place of Publication:Boca Raton
- Language:eng
- Publication Date:©2004.
The Physical Object
- Description:xiv, 333 pages : : illustrations ; : 24 cm.
Edition Identifiers
- ISBN:1584884339, 9781584884330, 9780203496862, 0203496868
- oclc:ocm52127752
- LC Classification:RA652.2.M3
- Dewey Decimal:614.4/072/7
Table of Contents
1. Introduction -- 2. Measures of disease occurrence -- 3. The role of probability in observational studies -- 4. Measures of disease-exposure association -- 5. Study designs -- 6. Assessing significance in a 2x2 table -- 7. Estimation and inference for measures of association -- 8. Causal inference and extraneous factors: Confounding and interaction -- 9. Control of extraneous factors -- 10. Interaction -- 11. Exposures at several discrete levels -- 12. Regression models relating exposure to disease -- 13. Estimation of logistic regression model parameters -- 14. Confounding and interaction within logistic regression models -- 15. Goodness of fit tests for logistic regression models and model building -- 16. Matched studies -- 17. Alternatives and extensions to the logistic regression model -- 18. Epilogue: The examples.
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