Biostatistical Methods in Epidemiology

An introduction to classical biostatistical methods in epidemiology
Biostatistical Methods in Epidemiology provides an introduction to a wide range of methods used to analyze epidemiologic data, with a focus on nonregression techniques. The text includes an extensive discussion of measurement issues in epidemiology, especially confounding. Maximum likelihood, Mantel–Haenszel, and weighted least squares methods are presented for the analysis of closed cohort and case–control data. Kaplan–Meier and Poisson methods are described for the analysis of censored survival data. A justification for using odds ratio methods in case–control studies is provided. Standardization of rates is discussed and the construction of ordinary, multiple decrement and cause–deleted life tables is outlined. Sample size formulas are given for a range of epidemiologic study designs. The text ends with a brief overview of logistic and Cox regression. Other highlights include:
∗ Many worked examples based on actual data
∗ Discussion of exact methods
∗ Recommendations for preferred methods
∗ Extensive appendices and references
Biostatistical Methods in Epidemiology provides an excellent introduction to the subject for students, while also serving as a comprehensive reference for epidemiologists and other health professionals.
For more information, visit www.wiley.com/mathematics

Spis treści:
Introduction.
Measurement Issues in Epidemiology.
Binomial Methods for Single Sample Closed Cohort Data.
Odds Ratio Methods for Unstratified Closed Cohort Data.
Odds Ratio Methods for Stratified Closed Cohort Data.
Risk Ratio Methods for Closed Cohort Data.
Risk Difference Methods for Closed Cohort Data.
Survival Analysis.
Kaplan–Meier and Actuarial Methods for Censored Survival Data.
Poisson Methods for Censored Survival Data.
Odds Ratio Methods for Case–Control Data.
Standardized Rates and Age–Period–Cohort Analysis.
Life Tables.
Sample Size and Power.
Logistic Regression and Cox Regression.
Appendix A: Odds Ratio Inequality.
Appendix B: Maximum Likelihood Theory.
Appendix C: Hypergeometric and Conditional Poisson Distributions.
Appendix D: Quadratic Equation for the Odds Ratio.
Appendix E: Matrix Identities and Inequalities.
Appendix F: Survival Analysis and Life Tables.
Appendix G: Confounding in Open Cohort and Case–Control Studies.
Appendix H: Odds Ratio Estimate in a Matched Case–Control Study.
References.
Index.

Nota biograficzna:
STEPHEN C. NEWMAN, MD, MSc, is Professor of Psychiatry at the University of Alberta, Canada.

Okładka tylna:
An introduction to classical biostatistical methods in epidemiology
Biostatistical Methods in Epidemiology provides an introduction to a wide range of methods used to analyze epidemiologic data, with a focus on nonregression techniques. The text includes an extensive discussion of measurement issues in epidemiology, especially confounding. Maximum likelihood, Mantel–Haenszel, and weighted least squares methods are presented for the analysis of closed cohort and case–control data. Kaplan–Meier and Poisson methods are described for the analysis of censored survival data. A justification for using odds ratio methods in case–control studies is provided. Standardization of rates is discussed and the construction of ordinary, multiple decrement and cause–deleted life tables is outlined. Sample size formulas are given for a range of epidemiologic study designs. The text ends with a brief overview of logistic and Cox regression. Other highlights include:
∗ Many worked examples based on actual data
∗ Discussion of exact methods
∗ Recommendations for preferred methods
∗ Extensive appendices and references
Biostatistical Methods in Epidemiology provides an excellent introduction to the subject for students, while also serving as a comprehensive reference for epidemiologists and other health professionals.
For more information, visit www.wiley.com/mathematics