Epidemiologic Research

Principles and Quantitative Methods

Inbunden, Engelska, 1982

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Beskrivning

Epidemiologic Research Principles and Quantitative Methods DavidG. Kleinbaum, Ph.D. Lawrence L. Kupper. Ph.D. Hal Morgenstern,Ph.D. Epidemiologic Research covers the principles and methodsof planning, analysis and interpretation of epidemiologic researchstudies. It supplies the applied researcher with the mostup-to-date methodological thought and practice. Specifically, thebook focuses on quantitative (including statistical) issues arisingfrom epidemiologic investigations, as well as on the questions ofstudy design, measurement and validity. EpidemiologicResearch emphasizes practical techniques, procedures andstrategies. It presents them through a unified approach whichfollows the chronology of issues that arise during theinvestigation of an epidemic. The book's viewpoint ismultidisciplinary and equally useful to the epidemiologicresearcher and to the biostatistician. Theory is supplemented bynumerous examples, exercises and applications. Full solutions aregiven to all exercises in a separate solutions manual. Importantfeatures* Thorough discussion of the methodology of epidemiologicresearch* Stress on validity and hence on reliability* Balanced approach, presenting the most important prevailingviewpoints* Three chapters with applications of mathematical modeling

Produktinformation

Utgivningsdatum:1982-05-01
Mått:174 x 238 x 32 mm
Vikt:980 g
Format:Inbunden
Språk:Engelska
Antal sidor:560
Förlag:John Wiley & Sons Inc
ISBN:9780471289852

Utforska kategorier

Epidemiologi och medicinsk statistik inom Medicin

Mer om författaren

David G. Kleinbaum is Associate Professor of Biostatisticsand Epidemiology at the University of North Carolina School ofPublic Health and holds a Ph.D. from the University of NorthCarolina. Lawrence L. Kupper is Professor of Biostatistics andEpidemiology at the University of North Carolina School of PublicHealth and holds a Ph.D. from the University of North Carolina.Drs. Kleinbaum and Kupper have worked on the development ofapplications of statistical methods to epidemiology for over tenyears. They have conducted several epidemiological research studiesand published their work in Biometrics and the American Journal ofEpidemiology, among others. Their short course on the subject ofthis book is in high demand in the U.S. and internationally. Theyare also the authors of Applied Regression Analysis (Duxbury Press,1977). Hal Morgenstern is Assistant Professor of Epidemiology atthe Yale University School of Public Health. Dr.Morgenstern's work focuses on epidemiologic research methodsand he has published extensively on the subject in the AmericanJournal of Epidemiology, the International Journal of Epidemiology,Biometrics and the Journal of Community Health. Much of hisresearch is applied to planning and policy issues, as well as tocardiovascular disease and to senile dementia. Dr. Morgensternholds a Ph.D. in Epidemiology from the University of NorthCarolina, as well as degrees in Architecture from M.I.T. and inRegional Planning from the University of North Carolina.

Innehållsförteckning

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. Confounding Involving Several Risk Factors. PRINCIPLES AND PROCEDURES OF EPIDEMIOLOGIC ANALYSIS. Statistical Inferences About Effect Measures: SimpleAnalysis. 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, UsingUnconditional ML Estimation. Applications of Modeling: Conditional Likelihood Estimation. Appendices. Index.