The use of client surveys to gauge the threat of contamination in welfare reform experiments
Bibliographic Data
| ID | 11680439 |
|---|---|
| Authors | Michael J Camasso (Rutgers Sexual and Reproductive Health and Rights, corresponding author), Ram Jagannathan (0000-0001-5614-8176, Rutgers, the State University of New Jersey), Carol Harvey (0000-0002-5066-8450, Rutgers Sexual and Reproductive Health and Rights), Mark R Killingsworth (Rutgers Sexual and Reproductive Health and Rights), Mark Killingsworth |
| Year | 2003 |
| Volume | 22 |
| Issue | 2 |
| Pages | 207-223 |
| Publication date | 2003-03-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Policy Analysis and Management (JOURNAL) |
| Journal identifiers | ISSN: 0276-8739 • E-ISSN: 1520-6688 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/pam.10114 |
| OpenAlex | W2135784831 |
| Language | EN |
| Citations received | 9 |
| References cited | 14 |
This paper examines the type of evidence policy analysts have used to identify the presence and magnitude of contamination in welfare reform experiments. Peter Rossi's critique of the New Jersey Family Development Program evaluation motivates the following discussion. In this critique Rossi and others contend that client misperception about experimental control‐group assignment resulted in contamination that negates reported treatment effectiveness. By applying the framework of the Rubin Causal Model (RCM) to isolate “pure” and “impure” experimental and control cases, the actual group assignment and not self‐reported membership is shown to be a more accurate gauge of treatment level and effect. The analysis reveals that the form of contamination Rossi detected leads to underestimates of treatment effects, not their evaporation. While contamination is a legitimate threat in any research design its identification must be based on empirical measures. © 2003 by the Association for Public Policy Analysis and Management
Actuarial science · Association (psychology · Biology · Business · Contamination · Control (management · Economics · Gauge (firearms · Identification (biology · Management · Political science · Public economics · Statistics · Treatment and control groups · Welfare · Advanced Causal Inference Techniques · Gender, Labor, and Family Dynamics · Healthcare Policy and Management · History · Law · Mathematics · Psychology · Ecology
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| Unique citing works | 9 |
|---|---|
| Citations per year | 0,39 |
| Citation span | 2003 - 2010 (8) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 9 |