Observation and experiment
Subtitle: an introduction to causal inference
By: Paul R. Rosenbaum
Published: 2017
Language: eng
Number of pages: 374
ISBN-13: 9780674975576
Copyright date: 2017
Subjects: Experiments; Inference; Probabilities; Science; Causation; Observation (Scientific method)
Description: We hear that a glass of red wine prolongs life, that alcohol is a carcinogen, that pregnant women should drink not a drop of alcohol. Major medical journals first claimed that hormone replacement therapy reduces the risk of heart disease, then reversed themselves and said it increases the risk of heart disease. What are the effects caused by consuming alcohol or by receiving hormone replacement therapy? These are causal questions, questions about the effects caused by treatments, policies or preventable exposures. Some causal questions can be studied in randomized trials, in which a coin is flipped to decide the treatment for the next experimental subject. Because randomized trials are not always practical, nor always ethical, many causal questions are investigated in non-randomized observational studies. The reversal of opinion about hormone replacement therapy occurred when a randomized clinical trial contradicted a series of earlier observational studies. Using minimal mathematics--high school algebra and coin flips--and numerous examples, Observation and Experiment explains the key concepts and methods of causal inference. Examples of randomized experiments and observational studies are drawn from clinical medicine, economics, public health and epidemiology, clinical psychology and psychiatry.--
Notes: Includes bibliographical references and index.
Table of contents: title: Part I. Randomized experiments. A randomized trial; title: Structure; title: Causal inference in randomized experiments; title: Irrationality and polio; title: Part II. Observational studies. Between observational studies and experiments; title: Natural experiments; title: Elaborate theories; title: Quasi-experimental devices; title: Sensitivity to bias; title: Design sensitivity; title: Matching techniques; title: Biases from general dispositions; title: Instruments; title: Conclusion.