| Dewey Class |
519.5 |
| Titolo |
Observational Studies ([EBook] /) / by Paul R. Rosenbaum. |
| Autore |
Rosenbaum, Paul R. |
| Other name(s) |
SpringerLink (Online service) |
| Edition statement |
Second Edition. |
| Pubblicazione |
New York, NY : : Springer New York : : Imprint: Springer, , 2002. |
| Physical Details |
XIV, 377 p. 6 illus. : online resource. |
| Serie |
Springer Series in Statistics 0172-7397 |
| ISBN |
9781475736922 |
| Summary Note |
An observational study is an empiric investigation of the effects caused by a treatment, policy, or intervention in which it is not possible to assign subjects at random to treatment or control, as would be done in a controlled experiment. Observational studies are common in most fields that study the effects of treatments on people. The second edition of Observational Studies is about 50% longer than the first edition, with many new examples and methods. There are new chapters on nonadditive models for treatment effects (5) and planning observational studies , and the chapter on coherence (9) has been extensively rewritten. Paul R. Rosenbaum is Robert G. Putzel Professor, Department of Statistics, The Wharton School of the University of Pennsylvania. He is a fellow of the American Statistical Association.: |
| Contents note |
1 Observational Studies -- 2 Randomized Experiments -- 3 Overt Bias in Observational Studies -- 4 Sensitivity to Hidden Bias -- 5 Models for Treatment Effects -- 6 Known Effects -- 7 Multiple Reference Groups in Case-Referent Studies -- 8 Multiple Control Groups -- 9 Coherence and Focused Hypotheses -- 10 Constructing Matched Sets and Strata -- 11 Planning an Observational Study -- 12 Some Strategic Issues. |
| System details note |
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users) |
| Internet Site |
http://dx.doi.org/10.1007/978-1-4757-3692-2 |
| Link alle Opere Legate |
Riferimenti soggetto: .
Statistical Theory and Methods .
Statistics .
Statistics for Business/Economics/Mathematical Finance/Insurance .
Statistics for Life Sciences, Medicine, Health Sciences .
Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law .
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