- 巻冊次
-
: hbk ISBN 9780195135534
内容説明
During the last 30 years of the 20th century, epidemiology has matured from fledging 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. This book aims to close 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 measures of disease occurrence and causal effects. With these building blocks in place, the reader learns how to design, analyze and interpret epidemiologic research studies, and how to deal with the fundamental 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.
目次
1: Introduction to Epidemiologic Thinking. 2: What is Causation?. 3: Measuring Disease Occurrence and Causal Effects. 4: Types of Epidemiologic Studies. 5: Biases of Study Design. 6: Random Error and Role of Statistics. 7: Analyzing Simple Epidemiologic Data. 8: Controlling Confounding by Stratifying Data. 9: Measuring Interactions. 10: Using Regression Models in Epidemiologic Analysis. 11: Epidemiology in Clinical Settings
- 巻冊次
-
: pbk ISBN 9780195135541
内容説明
In 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 casual 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 epidemiologic research studies, and how to deal with the fundamental 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.
目次
- 1. Introduction to Epidemiologic Thinking
- 2. What is Causation?
- 3. Measuring Disease Occurrence and Causal Effects
- 4. Types of Epidemiologic Study
- 5. Biases of Study Design
- 6. Random Error and the Role of Statistics
- 7. Analyzing Simple Epidemiologic Data
- 8. Controlling Confounding by Stratifying Data
- 9. Measuring Interactions
- 10. Using Regression Models in Epidemiologic Analysis
- 11. Epidemiology in Clinical Settings
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