- Year: 2013
- Page Number: 758
- File Type: PDF
- File Size: 3.71 MB
- Authors/ Editiors: Kenneth J. Rothman
The thoroughly revised and updated Third Edition of the acclaimed Modern Epidemiology reflects both the conceptual development of this evolving science and the increasingly focal role that epidemiology plays in dealing with public health and medical problems. Coauthored by three leading epidemiologists, with contributions from sixteen experts in a variety of epidemiologic sub-disciplines, this new edition is by far the most comprehensive and cohesive text on the principles and methods of epidemiologic research.
The book covers a broad range of concepts and methods, including epidemiologic measures of occurrence and effect, study designs, validity, precision, statistical interference, and causal diagrams. Topics in data analysis range from Bayesian analysis, sensitivity analysis, and bias analysis, with an extensive overview of modern regression methods including logistic and survival regression, splines, hierarchical (multilevel) regression, propsensity scores and other scoring methods, and g-estimation. Special-topics chapters cover disease surveillance, ecologic studies, social epidemiology, infectious disease epidemiology, genetic and molecular epidemiology, nutritional epidemiology, environmental epidemiology, reproductive epidemiology, clinical epidemiology, and meta-analysis.
I am a social scientist, not an epidemiologist, and I found this book to exceptionally good. It is the most current, complete, and clear presentation of methods for causal inference for observational (i.e. non-experimental) studies that I have seen. The things that really set this book apart for me include:
1. It synthesizes contributions by Pearl and Rubin on the foundations of causal inference, and contributes its own perspective via the sufficient cause model. This is truly cutting edge, not to mention impeccably coherent.
2. The first third of the book is on study design, including measurement, sampling, and defining effects. This is just fantastic. Many methods textbooks jump right into approaches to analyzing data with little time taken to discuss how to make the data in the first place. This book provides a major corrective to that tendency.
3. In data analysis, a lot of attention is given to sparse data problems, which again is just great. So many textbooks overlook this problem, which is a huge omission.
4. The data analysis section includes discussion of up-and-coming data mining and non-parametric methods (e.g. BART, boosted regression, etc.) to characterize response surfaces in the service of causal inference. That’s amazingly cutting edge for a textbook.
5. The meta-analysis section emphasizes simplicity and provides a very nice list of common errors that should be avoided.
6. The references are to state of the art literature not only in epidemiology, but also in econometrics, education research, and statistics. It’s great to see such cross-fertilization across disciplines, and it shows how these various disciplines are converging, it seems, on common analytical tools for causal inference in observational studies.
There are lots of nice examples throughout the book too. For other social scientists out there, I highly recommend this as a primer on state of the art methods for carrying out observational studies.
This is an outstanding textbook, explaining the state-of-the-art thinking in Epidemiology. I am giving it 4 stars, because the book is quite dense and you basically have to read most chapters several times to really understand what they are saying!
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Free Download Modern Epidemiology – 3rd Edition in PDF format
Modern Epidemiology – 3rd Edition PDF Free Download
Download Modern Epidemiology – 3rd Edition 2013 PDF Free
Modern Epidemiology – 3rd Edition 2013 PDF Free Download
Download Modern Epidemiology – 3rd Edition PDF