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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... nonsmokers. The data are reproduced in Table 1–1. Only 24% of the women who were smokers at the time of the initial survey died during the 20year followup period. In contrast, 31%. SOURCE: U.S. Census Bureau, International Data Base. One ...
... nonsmokers. The data are reproduced in Table 1–1. Only 24% of the women who were smokers at the time of the initial survey died during the 20year followup period. In contrast, 31%. SOURCE: U.S. Census Bureau, International Data Base. One ...
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... nonsmokers died during the followup period. Does this difference indicate that women who were smokers fared better than women who were not smokers? Not necessarily. One difficulty that many researchers quickly spot is that the smoking ...
... nonsmokers died during the followup period. Does this difference indicate that women who were smokers fared better than women who were not smokers? Not necessarily. One difficulty that many researchers quickly spot is that the smoking ...
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... nonsmokers reflects the fact that, for most people, lifelong smoking habits are determined early in life. During the decades preceding the study in Whickham, there was a trend for increasing proportions of young women to become smokers ...
... nonsmokers reflects the fact that, for most people, lifelong smoking habits are determined early in life. During the decades preceding the study in Whickham, there was a trend for increasing proportions of young women to become smokers ...
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... nonsmokers. We say that smoking has a weaker effect on myocardial infarction because the risk of a heart attack is only about twice as great in smokers as in nonsmokers. With respect to an individual case of disease, however, every ...
... nonsmokers. We say that smoking has a weaker effect on myocardial infarction because the risk of a heart attack is only about twice as great in smokers as in nonsmokers. With respect to an individual case of disease, however, every ...
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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