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. |
From inside the book
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... Figure 1–1 shows the population pyramids of the two countries. A population pyramid displays the age distribution of a population graphically. The population pyramid for Panama tapers dramatically from younger to older age groups ...
... Figure 1–1 shows the population pyramids of the two countries. A population pyramid displays the age distribution of a population graphically. The population pyramid for Panama tapers dramatically from younger to older age groups ...
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An Introduction Kenneth J. Rothman. Figure 1–1 Age distribution of the populations of Panama and Sweden (population pyramids). This situation illustrates what epidemiologists call confounding. In this example, age differences between the ...
An Introduction Kenneth J. Rothman. Figure 1–1 Age distribution of the populations of Panama and Sweden (population pyramids). This situation illustrates what epidemiologists call confounding. In this example, age differences between the ...
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... of view. The longlived conductors who were cited in the article were mentioned because they lived to be old. One day, readers of the Boston Globe opened the paper to find a feature Figure 3–1 Three sufficient causes of a disease.
... of view. The longlived conductors who were cited in the article were mentioned because they lived to be old. One day, readers of the Boston Globe opened the paper to find a feature Figure 3–1 Three sufficient causes of a disease.
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... figure using five different approaches. 4. He invited readers to criticize his work, to “correct my Positions, and raise others of their own: For herein I have, like a silly Scholeboy, coming to say my Lesson to the World (that Peevish ...
... figure using five different approaches. 4. He invited readers to criticize his work, to “correct my Positions, and raise others of their own: For herein I have, like a silly Scholeboy, coming to say my Lesson to the World (that Peevish ...
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... of public health throughout India. Her work was characteristically meticulous, grounded in carefully collected data, and presented in compelling graphics. Figure 2–1. Diagram of mortality by cause during the Crimean.
... of public health throughout India. Her work was characteristically meticulous, grounded in carefully collected data, and presented in compelling graphics. Figure 2–1. Diagram of mortality by cause during the Crimean.
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