Epidemiologic Research: Principles and Quantitative Methods

Epidemiologic Research Principles and Quantitative Methods David G. Kleinbaum, Ph.D. Lawrence L. Kupper. Ph.D. Hal Morgenstern, Ph.D.
Epidemiologic Research covers the principles and methods of planning, analysis and interpretation of epidemiologic research studies. It supplies the applied researcher with the most up–to–date methodological thought and practice. Specifically, the book focuses on quantitative (including statistical) issues arising from epidemiologic investigations, as well as on the questions of study design, measurement and validity. Epidemiologic Research emphasizes practical techniques, procedures and strategies. It presents them through a unified approach which follows the chronology of issues that arise during the investigation of an epidemic. The book’s viewpoint is multidisciplinary and equally useful to the epidemiologic researcher and to the biostatistician. Theory is supplemented by numerous examples, exercises and applications. Full solutions are given to all exercises in a separate solutions manual. Important featuresThorough discussion of the methodology of epidemiologic researchStress on validity and hence on reliabilityBalanced approach, presenting the most important prevailing viewpointsThree chapters with applications of mathematical modeling

Spis treści:
Key Issues in Epidemiologic Research: An Overview.
OBJECTIVES AND METHODS OR EPIDEMIOLOGIC RESEARCH.
Fundamentals of Epidemiologic Research.
Types of Epidemiologic Research.
Design Options in Observational Studies.
Typology of Observational Study Designs.
Measures of Disease Frequency: Incidence.
Other Measures of Disease Frequency.
Measures of Association.
Measures of Potential Impact and Summary of the Measures.
VALIDITY OF EPIDEMIOLOGIC RESEARCH.
Validity: General Considerations.
Selection Bias.
Information Bias.
Confounding.
Confound ing Involving Several Risk Factors.
PRINCIPLES AND PROCEDURES OF EPIDEMIOLOGIC ANALYSIS.
Statistical Inferences About Effect Measures: Simple Analysis.
Overview of Options for Control of Extraneous Factors.
Stratified Analysis.
Matching in Epidemiologic Studies.
Interaction, Effect Modification, and Synergism.
Modeling: Theoretical Considerations.
Modeling: Analysis Strategy.
Applications of Modeling with No Interaction.
Applications of Logistic Regression with Interaction, Using Unconditional ML Estimation.
Applications of Modeling: Conditional Likelihood Estimation.
Appendices.
Index.

Nota biograficzna:
David G. Kleinbaum is Associate Professor of Biostatistics and Epidemiology at the University of North Carolina School of Public Health and holds a Ph.D. from the University of North Carolina.
Lawrence L. Kupper is Professor of Biostatistics and Epidemiology at the University of North Carolina School of Public Health and holds a Ph.D. from the University of North Carolina. Drs. Kleinbaum and Kupper have worked on the development of applications of statistical methods to epidemiology for over ten years. They have conducted several epidemiological research studies and published their work in Biometrics and the American Journal of Epidemiology, among others. Their short course on the subject of this book is in high demand in the U.S. and internationally. They are also the authors of Applied Regression Analysis (Duxbury Press, 1977).
Hal Morgenstern is Assistant Professor of Epidemiology at the Yale University School of Public Health. Dr. Morgenstern’s work focuses on epidemiologic research methods and he has published extensively on the subject in the American Journal of Epidemiology, the International Journal of Epidemiology, Biometrics and the Journal of Community Health. Much of his research is applied to planning and policy issues, as well as to cardiovascular disease and to senile dementia. Dr. Morgenstern holds a Ph.D. in Epidemiology from the University of North Carolina, as well as degrees in Architecture from M.I.T. and in Regional Planning from the University of North Carolina.