Epidemiology: An IntroductionAcross the last forty years, epidemiology has developed into a vibrant scientific discipline that brings together the social and biological sciences, incorporating everything from statistics to the philosophy of science in its aim to study and track the distribution and determinants of health events. A now-classic text, the second edition of this essential introduction to epidemiology presents the core concepts in a unified approach that aims to cut through the fog and elucidate the fundamental concepts. Rather than focusing on formulas or dogma, the book presents basic epidemiologic principles and concepts in a coherent and straightforward exposition. By emphasizing a unifying set of ideas, students will develop a strong foundation for understanding the principles of epidemiologic research. |
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... risk of cancer in the general population. Looking at the age at which cancer develops among those who get cancer ... factors? 2. More people in Los Angeles die from cardiovascular disease each year than do people in San Francisco. What is the ...
... risk of cancer in the general population. Looking at the age at which cancer develops among those who get cancer ... factors? 2. More people in Los Angeles die from cardiovascular disease each year than do people in San Francisco. What is the ...
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... risk factors for breast cancer.17 She selected 500 cases and an equal number of controls from hospitals in London and Glasgow. Exposure information was obtained by interview using a questionnaire designed for the study. Her analyses ...
... risk factors for breast cancer.17 She selected 500 cases and an equal number of controls from hospitals in London and Glasgow. Exposure information was obtained by interview using a questionnaire designed for the study. Her analyses ...
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... factors, such as the force of the wind, are environmental (nongenetic) ... factors that determine disease are taken into account, essentially 100% of disease can be said to be inherited, in the sense that nearly all cases ... risk with time.
... factors, such as the force of the wind, are environmental (nongenetic) ... factors that determine disease are taken into account, essentially 100% of disease can be said to be inherited, in the sense that nearly all cases ... risk with time.
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... factors in the causation of disease. One way this concept is expressed is by the strength of a causal effect. We say that smoking has a strong effect on lung cancer risk because smokers have about 10 times the risk of lung cancer as ...
... factors in the causation of disease. One way this concept is expressed is by the strength of a causal effect. We say that smoking has a strong effect on lung cancer risk because smokers have about 10 times the risk of lung cancer as ...
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Contents
Measuring Disease Occurrence and Causal Effects | |
Types of Epidemiologic Studies | |
Infectious Disease Epidemiology | |
Dealing with Biases | |
Random Error and the Role of Statistics | |
Controlling Confounding by Stratifying Data | |
Measuring Interactions | |
Using Regression Models in Epidemiologic Analysis | |
13 | |
Epidemiology in Clinical Settings | |
Appendix | |
Index | |
Analyzing Simple Epidemiologic Data | |
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Common terms and phrases
age categories age distribution asbestos attributable fraction biologic interaction birth order breast cancer calculated casecontrol data casecontrol study causal mechanisms Chapter cholera cigarette smoking clinical cohort study compared component causes confidence interval confounding factor control confounding control series curve data in Table denominator described effect epidemic epidemiologic epidemiologic study evaluation example experiment exposed and unexposed Figure flutamide incidence proportion incidence rate ratio infection influenza investigator lung cancer matching measure misclassification mortality rate myocardial infarction nonsmokers null hypothesis obtain occur odds ratio outbreak outcome patients person persontime personyears placebo pooled estimate population at risk predicted prevalence propensity score public health Pvalue function random assignment randomized trial rate difference rate ratio regression model relation result risk data risk difference risk factors risk of death risk ratio sampling selection bias significance testing source population specific standard statistical significance strata stratified analysis subjects Suppose tolbutamide treatment unexposed group vaccine variable women