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Attrition Bias in Experimental and Panel Data: The Gary Income Maintenance Experiment
Overview
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Citations
Cited by
Natural and Quasi-Experiments in Economics
Meyer, B. D. (1995) · Journal of Business & Economic Statistics · doi:10.1080/07350015.1995.10524589 · Cited by 1,100
On structural equation modeling with data that are not missing completely at random
Muthén, B., Kaplan, D., & Hollis, M. (1987) · Psychometrika · doi:10.1007/bf02294365 · Cited by 883
Accounting for No-Shows in Experimental Evaluation Designs
Bloom, H. S. (1984) · Evaluation Review · doi:10.1177/0193841x8400800205 · Cited by 532
Why We Should Not Be Indifferent to Specification Choices for Difference‐in‐Differences
Ryan, A. M., Burgess, J. F., & Dimick, J. B. (2015) · Health Services Research · doi:10.1111/1475-6773.12270 · Cited by 320
Better LATE Than Nothing: Some Comments on Deaton (2009) and Heckman and Urzua (2009)
Imbens, G. W. (2010) · Journal of Economic Literature · doi:10.1257/jel.48.2.399 · Cited by 278
Metadata
- Authors
- Hausman, J. A., & Wise, D. A.
- Venue
- Econometrica
- Publisher
- JSTOR
- Published
- 1979-03
- Volume
- 47
- Issue
- 2
- Pages
- 455
- ISSN
- 0012-9682 (ISSN-L)
- OpenAlex
- W2061127918
- Cited by
- 494
- References
- 0
- FWCI
- 7.60
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Attrition Bias in Experimental and Panel Data: The Gary Income Maintenance Experiment. https://app.cochat.ai/papers/10.2307/1914193
- The paper
- Hausman, J. A., & Wise, D. A. (1979). Attrition Bias in Experimental and Panel Data: The Gary Income Maintenance Experiment. Econometrica. https://doi.org/10.2307/1914193
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
