Epidemiology: An IntroductionIn the past thirty years epidemiology has matured from a fledgling scientific field into a vibrant discipline that brings together the biological and social sciences, and in doing so draws upon disciplines ranging from statistics and survey sampling to the philosophy of science. These areas of knowledge have converged into a modern theory of epidemiology that has been slow to penetrate into textbooks, particularly at the introductory level. Epidemiology: An Introduction closes the gap. It begins with a brief, lucid discussion of causal thinking and causal inference and then takes the reader through the elements of epidemiology, focusing on the measures of disease occurrence and causal effects. With these building blocks in place, the reader learns how to design, analyze and interpret problems that epidemiologists face, including confounding, the role of chance, and the exploration of interactions. All these topics are layered on the foundation of basic principles presented in simple language, with numerous examples and questions for further thought. |
From inside the book
Results 1-5 of 46
Page 1
... distributions of the populations of Sweden and Panama . Figure 1-1 shows the population pyramids of the two countries . A population pyramid displays the age distribution of a popula- tion graphically . The population pyramid for Panama ...
... distributions of the populations of Sweden and Panama . Figure 1-1 shows the population pyramids of the two countries . A population pyramid displays the age distribution of a popula- tion graphically . The population pyramid for Panama ...
Page 2
... distribution of the populations of Panama and Sweden ( population pyramids ) . Source : U.S. Census Bureau , International Data Base . a given year , despite the lower death rates within age categories in Sweden compared with Panama ...
... distribution of the populations of Panama and Sweden ( population pyramids ) . Source : U.S. Census Bureau , International Data Base . a given year , despite the lower death rates within age categories in Sweden compared with Panama ...
Page 3
... distributions between smokers and nonsmokers reflects the fact that , for most people , lifelong smoking habits are determined early in life . During the decades preced- Table 1-2 . Risk of death in a 20 - Introduction to Epidemiologic ...
... distributions between smokers and nonsmokers reflects the fact that , for most people , lifelong smoking habits are determined early in life . During the decades preced- Table 1-2 . Risk of death in a 20 - Introduction to Epidemiologic ...
Page 4
... distribution for the female smokers and non- smokers of Whickham . Were this difference in the age distribution ig- nored , one might conclude erroneously that smoking was not related to a higher risk of death . In fact , smoking is ...
... distribution for the female smokers and non- smokers of Whickham . Were this difference in the age distribution ig- nored , one might conclude erroneously that smoking was not related to a higher risk of death . In fact , smoking is ...
Page 11
... factor causes , which we use to define the strength of a cause , can change from population to population and over time if there are changes in the distribution of other causes of the disease . What Is Causation ? 11.
... factor causes , which we use to define the strength of a cause , can change from population to population and over time if there are changes in the distribution of other causes of the disease . What Is Causation ? 11.
Contents
1 | |
8 | |
3 Measuring Disease Occurrence and Causal Effects | 24 |
4 Types of Epidemiologic Study | 57 |
5 Biases in Study Design | 94 |
6 Random Error and the Role of Statistics | 113 |
7 Analyzing Simple Epidemiologic Data | 130 |
8 Controlling Confounding by Stratifying Data | 144 |
9 Measuring Interactions | 168 |
10 Using Regression Models in Epidemiologic Analysis | 181 |
11 Epidemiology in Clinical Settings | 198 |
Appendix | 218 |
Index | 221 |
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Common terms and phrases
age categories asbestos attributable fraction average baseline bias biologic interaction birth order breast cancer calculate case-control data case-control study causal causal mechanism Chapter cigarette smoking clozapine cohort study compared component causes confidence interval confidence limits control confounding control series crude data curve data in Table dence rate denominator described distribution drug epidemic epidemiologic epidemiologic study evaluation example experiment exposed and unexposed exposed group Figure flutamide follow-up formula imbalance inci incidence proportion incidence rate ratio inference laryngeal cancer leukemia lung cancer measure misclassification mortality rate myocardial infarction nonsmokers null hypothesis obtain occur odds ratio outcome patients person person-time person-years placebo pooled estimate population at risk predict prevalence random error randomized trial rate difference relation result risk data risk difference risk factor risk of death risk ratio Rothman sampling screening source population specific standard strata stratified analysis Suppose syndrome tamoxifen tion tolbutamide treatment value function variable women