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Learning more from social experiments : evolving analytic approaches /
"Using evaluations of actual social programs as examples, Learning More from Social Experiments makes the case that many of the limitations of random-assignment studies can be overcome by combining data from these studies with statistical methods from other research designs." "Bloom e...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York :
Russell Sage Foundation,
©2005.
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| Colección: | UPCC book collections on Project MUSE.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 245 | 0 | 0 | |a Learning more from social experiments : |b evolving analytic approaches / |c Howard S. Bloom, editor. |
| 260 | |a New York : |b Russell Sage Foundation, |c ©2005. | ||
| 300 | |a 1 online resource (xi, 246 pages :) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Contributors; Preface; Chapter 1. Precedents and Prospects for Randomized Experiments -- Charles Michalopoulos; Chapter 2. Modeling Cross-Site Experimental Differences to Find Out Why Program Effectiveness Varies -- Howard S. Bloom, Carolyn J. Hill, and James A. Riccio; Chapter 3. Constructing Instrumental Variables from Experimental Data to Explore How Treatments Produce Effects -- Lisa A. Gennetian, Pamela A. Morris, Johannes M. Bos, and Howard S. Bloom; Chapter 4. Randomizing Groups to Evaluate Place-Based Programs -- Howard S. Bloom. | |
| 505 | 8 | |a Chapter 5. Using Experiments to Assess Nonexperimental Comparison-Group Methods for Measuring Program Effects -- Howard S. Bloom, Charles Michalopoulos, and Carolyn J. HillIndex. | |
| 520 | 1 | |a "Using evaluations of actual social programs as examples, Learning More from Social Experiments makes the case that many of the limitations of random-assignment studies can be overcome by combining data from these studies with statistical methods from other research designs." "Bloom evaluates the properties of cluster randomization, its relevance to different kinds of social programs, and the complications that arise from its use. He pays particular attention to the way in which the movement of individuals into and out of clusters over time complicates the design, execution, and interpretation of a study."--Jacket. | |
| 546 | |a English. | ||
| 590 | |a JSTOR |b Books at JSTOR All Purchased | ||
| 590 | |a JSTOR |b Books at JSTOR Demand Driven Acquisitions (DDA) | ||
| 650 | 0 | |a Experimental design. | |
| 650 | 0 | |a Social sciences |x Research. | |
| 650 | 0 | |a Social sciences |x Experiments. | |
| 650 | 6 | |a Plan d'expérience. | |
| 650 | 6 | |a Sciences sociales |x Recherche. | |
| 650 | 7 | |a SOCIAL SCIENCE |x Methodology. |2 bisacsh | |
| 650 | 7 | |a Experimental design. |2 fast |0 (OCoLC)fst00918404 | |
| 650 | 7 | |a Social sciences |x Experiments. |2 fast |0 (OCoLC)fst01122913 | |
| 650 | 7 | |a Social sciences |x Research. |2 fast |0 (OCoLC)fst01122944 | |
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| 650 | 7 | |a Social Sciences - General. |2 hilcc | |
| 653 | |a "An MDRC project." | ||
| 653 | |a "Multi-User" | ||
| 700 | 1 | |a Bloom, Howard S. | |
| 776 | 0 | 8 | |i Print version: |t Learning more from social experiments. |d New York : Russell Sage Foundation, ©2005 |w (DLC) 2004061463 |
| 830 | 0 | |a UPCC book collections on Project MUSE. | |
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