The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Regression-discontinuity analysis: An alternative to the ex post facto experiment.
Abstract
This study presents a method of testing casual hypotheses, called regression-discontinuity analysis, in situations where the investigator is unable to randomly assign Ss to experimental and control groups. The Ss were selected from near winners--5126 students who received certificates of merit and 2
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“There is now a large family of designs for testing efficacy or effectiveness that randomize across persons, place, and time (or combinations of these) (15), as well as designs that do not use randomization, such as pre-post comparisons, regression discontinuity (106), time series and multiple baseline comparisons (5).”
From An Overview of Research and Evaluation Designs for Dissemination and Implementation (2017) · cites this paper as [106]
Citations
Cites
Introduction to the Theory of Statistics.
Wolfowitz, J., & Mood, A. M. (1951) · American Mathematical Monthly · doi:10.2307/2307742 · Cited by 543
Introduction to the Theory of Statistics
Rutherford, R. S. G., & Mood, A. M. (1951) · The Australian Quarterly · doi:10.2307/20633337 · Cited by 297
Regression Fallacies in the Matched Groups Experiment
Thorndike, R. L. (1942) · Psychometrika · doi:10.1007/bf02288069 · Cited by 93
Wilkins, L. T., Walker, H. M., & Lev, J. (1954) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.2307/2985384 · Cited by 69
Experimental Sociology: A Study in Method.
Kendall, P. L., & Greenwood, E. (1945) · American Sociological Review · doi:10.2307/2085603 · Cited by 50
Chapin, F. S. (1938) · American Sociological Review · doi:10.2307/2084712 · Cited by 21
Experimental Sociology; A Study in Method
Brighouse, G., & Greenwood, E. (1946) · The American Journal of Psychology · doi:10.2307/1416902 · Cited by 19
Effects of social recognition upon the educational motivation of talented youth.
Thistlethwaite, D. L. (1959) · Journal of Educational Psychology · doi:10.1037/h0042153 · Cited by 12
Self-citationManella, F. L. (1960) · The American Catholic Sociological Review · doi:10.2307/3708624 · Cited by 5
Flagged first, then by citations
Cited by
Sorted by citations
Items 101–200 of 1,001
Hainmueller, J., & Kern, H. (2008) · Electoral Studies · doi:10.1016/j.electstud.2007.10.006 · Cited by 166
Battistin, E., & Rettore, E. (2007) · Journal of Econometrics · doi:10.1016/j.jeconom.2007.05.006 · Cited by 157
Omitted variable bias: A threat to estimating causal relationships
Wilms, R., Mäthner, E., Winnen, L., & Lanwehr, R. (2021) · Methods in Psychology · doi:10.1016/j.metip.2021.100075 · Cited by 196
Position Effects in Search Advertising and their Moderators: A Regression Discontinuity Approach
Narayanan, S., & Kalyanam, K. (2015) · Marketing Science · doi:10.1287/mksc.2014.0893 · Cited by 157
Cattaneo, M. D., Titiunik, R., & Vázquez-Baré, G. (2017) · Journal of Policy Analysis and Management · doi:10.1002/pam.21985 · Cited by 155
The Impact of Incarceration on Recidivism
Loeffler, C. E., & Nagin, D. S. (2021) · Annual Review of Criminology · doi:10.1146/annurev-criminol-030920-112506 · Cited by 156
Does Education Empower Women? Evidence from Indonesia
Samarakoon, S., & PARINDURI, R. A. (2014) · World Development · doi:10.1016/j.worlddev.2014.09.002 · Cited by 154
Program Evaluation and Research Designs
DiNardo, J., & Lee, D. (2010) · Handbook of labour economics · doi:10.1016/s0169-7218(11)00411-4 · Cited by 146
Identifying the Effect of Changing the Policy Threshold in Regression Discontinuity Models
Dong, Y., & Lewbel, A. (2015) · The Review of Economics and Statistics · doi:10.1162/rest_a_00510 · Cited by 150
Steiner, P. M., Cook, T. D., & Shadish, W. R. (2011) · Journal of Educational and Behavioral Statistics · doi:10.3102/1076998610375835 · Cited by 152
Ferreira, F. (2010) · Journal of Public Economics · doi:10.1016/j.jpubeco.2010.04.003 · Cited by 148
Punishment and Deterrence: Evidence from Drunk Driving
Hansen, B. (2015) · American Economic Review · doi:10.1257/aer.20130189 · Cited by 145
Rasmussen, A. W. (2009) · Labour Economics · doi:10.1016/j.labeco.2009.07.007 · Cited by 140
Valentine, J. C., & Thompson, S. G. (2013) · Research Synthesis Methods · doi:10.1002/jrsm.1064 · Cited by 130
Quantile treatment effects in the regression discontinuity design
Frandsen, B., Frölich, M., & Melly, B. (2012) · Journal of Econometrics · doi:10.1016/j.jeconom.2012.02.004 · Cited by 141
Do Payday Loans Cause Bankruptcy?
Skiba, P. M., & Tobacman, J. (2019) · The Journal of Law and Economics · doi:10.1086/706201 · Cited by 232
Remedial Education and Student Achievement: A Regression-Discontinuity Analysis
Jacob, B. A., & Lefgren, L. J. (2002) · National Bureau of Economic Research · doi:10.3386/w8918 · Cited by 136
The impact of NIH postdoctoral training grants on scientific productivity
Jacob, B. A., & Lefgren, L. J. (2011) · Research Policy · doi:10.1016/j.respol.2011.04.003 · Cited by 135
Evaluating Social Programs with Endogenous Program Placement and Selection of the TreatedPreprint
Todd, P. (2008) · RePEc: Research Papers in Economics · Cited by 130
Shadish, W. R. (2010) · Psychological Methods · doi:10.1037/a0015916 · Cited by 130
Lee, D. (2001) · National Bureau of Economic Research · doi:10.3386/w8441 · Cited by 130
Breaking the link between poverty and low student achievement: An evaluation of Title I
van der Klaauw, W. (2007) · Journal of Econometrics · doi:10.1016/j.jeconom.2007.05.007 · Cited by 129
Partisanship and confidence in the vote count: Evidence from U.S. national elections since 2000
Sances, M., & Stewart, C. H., III (2015) · Electoral Studies · doi:10.1016/j.electstud.2015.08.004 · Cited by 128
Fredriksson, P., & Öckert, B. (2005) · SSRN Electronic Journal · doi:10.2139/ssrn.760728 · Cited by 125
Threshold Events and Identification: A Study of Cash Shortfalls
Bakke, T., & Whited, T. M. (2012) · The Journal of Finance · doi:10.1111/j.1540-6261.2012.01742.x · Cited by 124
Cook, P. J., & Kang, S. (2015) · American Economic Journal Applied Economics · doi:10.1257/app.20140323 · Cited by 121
O’Keeffe, A. G., Geneletti, S., Baio, G., Sharples, L. D., Nazareth, I., & Petersen, I. (2014) · BMJ · doi:10.1136/bmj.g5293 · Cited by 119
Early kindergarten, maternal labor supply and children's outcomes: Evidence from Italy
Carta, F., & Rizzica, L. (2018) · Journal of Public Economics · doi:10.1016/j.jpubeco.2017.12.012 · Cited by 118
A Practical Introduction to Regression Discontinuity Designs
Cattaneo, M. D., Idrobo, N., & Titiunik, R. (2024) · Cambridge University Press eBooks · doi:10.1017/9781009441896 · Cited by 117
Cook, T. D., & Steiner, P. M. (2010) · Psychological Methods · doi:10.1037/a0018536 · Cited by 117
Natural experiments in leadership research: An introduction, review, and guidelines
Sieweke, J., & Santoni, S. (2019) · The Leadership Quarterly · doi:10.1016/j.leaqua.2019.101338 · Cited by 118
Education, earnings, and the ‘Canadian G.I. Bill’
Lemieux, T., & Card, D. (2001) · Canadian Journal of Economics/Revue canadienne d économique · doi:10.1111/0008-4085.00077 · Cited by 112
External Validity in Fuzzy Regression Discontinuity Designs
Bertanha, M., & Imbens, G. W. (2019) · Journal of Business and Economic Statistics · doi:10.1080/07350015.2018.1546590 · Cited by 110
Modern Regression Discontinuity Analysis
Bloom, H. S. (2012) · Journal of Research on Educational Effectiveness · doi:10.1080/19345747.2011.578707 · Cited by 110
The impact of national research funds: A regression discontinuity approach to the Chilean FONDECYT
Benavente, J. M., Crespi, G., Garone, L. F., & Maffioli, A. (2012) · Research Policy · doi:10.1016/j.respol.2012.04.007 · Cited by 109
Evaluating the Impact of Innovation Incentives: Evidence from an Unexpected Shortage of FundsPreprint
de Blasio, G., Fantino, D., & Pellegrini, G. (2011) · SSRN Electronic Journal · doi:10.2139/ssrn.1830001 · Cited by 109
Keele, L. J., Titiunik, R., & Zubizarreta, J. R. (2014) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/rssa.12056 · Cited by 109
Juvenile Jails: A Path to the Straight and Narrow or to Hardened Criminality?
Hjalmarsson, R. (2009) · The Journal of Law and Economics · doi:10.1086/596039 · Cited by 106
Cellini, S. R. (2009) · American Economic Journal Economic Policy · doi:10.1257/pol.1.2.1 · Cited by 105
Modernizing the Bradford Hill criteria for assessing causal relationships in observational data
Cox, L. A. (2018) · Critical Reviews in Toxicology · doi:10.1080/10408444.2018.1518404 · Cited by 107
Reynolds, C. L., & DesJardins, S. L. (2009) · Higher Education: Handbook of Theory and Research · doi:10.1007/978-1-4020-9628-0_2 · Cited by 104
Hohlfeld, T. N., Ritzhaupt, A. D., Dawson, K., & Wilson, M. L. (2017) · Computers & Education · doi:10.1016/j.compedu.2017.05.017 · Cited by 122
Quasi-experimental causality in neuroscience and behavioural research
Marinescu, I., Lawlor, P. N., & Kording, K. P. (2018) · Nature Human Behaviour · doi:10.1038/s41562-018-0466-5 · Cited by 107
Puranam, D., Narayan, V., & Kadiyali, V. (2017) · Marketing Science · doi:10.1287/mksc.2017.1048 · Cited by 104
Robertson, C., Savva, G. M., Clapuci, R., Jones, J. E., Maimouni, H., Brown, E., Minocha, A., Hall, L. J., & Clarke, P. (2019) · Archives of Disease in Childhood Fetal & Neonatal · doi:10.1136/archdischild-2019-317346 · Cited by 102
Reading First Impact Study Final Report
Gamse, B., Jacob, R. T., Horst, M. A., Boulay, B. A., Associates, A., Unlu, F., Bozzi, L., Caswell, L., Rodger, C., Carter, W., et al. (2009) · Cited by 100
Causal Inference and Omitted Variable Bias in Financial Aid Research: Assessing Solutions
Riegg, S. K. (2008) · Review of higher education/The review of higher education · doi:10.1353/rhe.2008.0010 · Cited by 99
Imbens, G. W. (2019) · National Bureau of Economic Research · doi:10.3386/w26104 · Cited by 103
Inclusion of quasi-experimental studies in systematic reviews of health systems research
Rockers, P. C., Røttingen, J., Shemilt, I., Tugwell, P., & Bärnighausen, T. (2014) · Health Policy · doi:10.1016/j.healthpol.2014.10.006 · Cited by 110
Global music streaming data reveal diurnal and seasonal patterns of affective preference
Park, M., Thom, J., Mennicken, S., Cramer, H. S. M., & Macy, M. W. (2019) · Nature Human Behaviour · doi:10.1038/s41562-018-0508-z · Cited by 97
Li, Y., Zhu, D., Zhao, J., Zheng, X., & Zhang, L. (2020) · Land Use Policy · doi:10.1016/j.landusepol.2020.104528 · Cited by 95
Econometrics for Evaluations: An Introduction to Recent Developments
Cobb‐Clark, D. A., & Crossley, T. F. (2003) · Economic Record · doi:10.1111/j.1475-4932.2003.00148.x · Cited by 97
Papay, J. P., Murnane, R. J., & Willett, J. B. (2010) · Educational Evaluation and Policy Analysis · doi:10.3102/0162373709352530 · Cited by 102
Evaluating the Effect of an Antidiscrimination Law Using a Regression-Discontinuity Design
Hahn, J., Todd, P., & van der Klaauw, W. (1999) · National Bureau of Economic Research · doi:10.3386/w7131 · Cited by 95
Zhuo, C., Xie, Y., Mao, Y., Chen, P., & Li, Y. (2021) · Energy Economics · doi:10.1016/j.eneco.2021.105803 · Cited by 94
Crime and Expected Punishment: Changes in Perceptions at the Age of Criminal Majority
Hjalmarsson, R. (2009) · American Law and Economics Review · doi:10.1093/aler/ahn016 · Cited by 92
Understanding College Application Decisions
Pope, D. G., & Pope, J. C. (2012) · Journal of Sports Economics · doi:10.1177/1527002512445569 · Cited by 94
Wing, C., & Cook, T. D. (2013) · Journal of Policy Analysis and Management · doi:10.1002/pam.21721 · Cited by 87
When does regression discontinuity design work? Evidence from random election outcomes
Hyytinen, A., Meriläinen, J., Saarimaa, T., Toivanen, O., & Tukiainen, J. (2018) · Quantitative Economics · doi:10.3982/qe864 · Cited by 91
Causal Inference in the Social Sciences
Imbens, G. W. (2023) · Annual Review of Statistics and Its Application · doi:10.1146/annurev-statistics-033121-114601 · Cited by 109
Testing the Accuracy of Regression Discontinuity Analysis Using Experimental Benchmarks
GREEN, D. P., Leong, T. Y., Kern, H., Gerber, A. S., & Larimer, C. W. (2009) · Political Analysis · doi:10.1093/pan/mpp018 · Cited by 90
Keele, L. J., & Minozzi, W. (2013) · Political Analysis · doi:10.1093/pan/mps041 · Cited by 86
Got Rejected? Real Effects of Not Getting a Loan
Berg, T. (2018) · Review of Financial Studies · doi:10.1093/rfs/hhy038 · Cited by 89
Pei, Z., Card, D., Lee, D. S., & Weber, A. M. (n.d.) · RePEc: Research Papers in Economics · Cited by 89
A Permutation Test for the Regression Kink Design
Ganong, P., & Jäger, S. (2017) · Journal of the American Statistical Association · doi:10.1080/01621459.2017.1328356 · Cited by 87
A randomized experiment comparing random and cutoff-based assignment.
Shadish, W. R., Galindo, R. J., Wong, V. C., Steiner, P. M., & Cook, T. D. (2011) · Psychological Methods · doi:10.1037/a0023345 · Cited by 86
Hullegie, P., & Klein, T. J. (2010) · Health Economics · doi:10.1002/hec.1642 · Cited by 86
Are we spending too much to grow? The case of Structural Funds
Cerqua, A., & Pellegrini, G. (2017) · Journal of Regional Science · doi:10.1111/jors.12365 · Cited by 85
Impact Evaluation of Development Interventions: A Practical Guide
(2017) · doi:10.22617/tcs179188-2 · Cited by 85
A robust interrupted time series model for analyzing complex health care intervention data
Cruz, M., Bender, M., & Ombao, H. (2017) · Statistics in Medicine · doi:10.1002/sim.7443 · Cited by 83
Does Financing Spur Small Business Productivity? Evidence from a Natural ExperimentPreprint
Krishnan, K., Nandy, D. K., & Puri, M. (2013) · SSRN Electronic Journal · doi:10.2139/ssrn.2358819 · Cited by 83
Chaplin, D., Cook, T. D., Zurovac, J., Coopersmith, J., Finucane, M. M., Vollmer, L., & Morris, R. E. (2018) · Journal of Policy Analysis and Management · doi:10.1002/pam.22051 · Cited by 81
Female education and maternal health care utilization: evidence from Uganda
Amwonya, D., Kigosa, N., & Kizza, J. (2022) · Reproductive Health · doi:10.1186/s12978-022-01432-8 · Cited by 82
Jones, N. M., Wojcik, S. P., Sweeting, J. A., & Silver, R. C. (2016) · Psychological Methods · doi:10.1037/met0000099 · Cited by 81
An assessment of some structural properties of the Jungian personality typology.
Stricker, L. J., & Ross, J. (1964) · Journal of Abnormal & Social Psychology · doi:10.1037/h0043580 · Cited by 81
Do Parties Matter? Estimating the Effect of Political Power in Multi-Party Systems
Freier, R., & Odendahl, C. (2012) · European Economic Review · doi:10.1016/j.euroecorev.2015.09.011 · Cited by 81
Qin, X., Zhuang, C. C., & Yang, R. (2016) · Journal of Comparative Economics · doi:10.1016/j.jce.2016.09.001 · Cited by 83
The Impact of Liquidity Regulation on Bank Intermediation
Bonner, C., & Eijffinger, S. C. W. (2015) · European Finance Review · doi:10.1093/rof/rfv058 · Cited by 79
Estimating Causal Impacts of School Counselors With Regression Discontinuity Designs
Hurwitz, M. D., & Howell, J. (2014) · Journal of Counseling & Development · doi:10.1002/j.1556-6676.2014.00159.x · Cited by 79
Berk, R. A., Barnes, G. C., Ahlman, L., & Kurtz, E. (2010) · Journal of Experimental Criminology · doi:10.1007/s11292-010-9095-3 · Cited by 78
Regression Discontinuity for Causal Effect Estimation in Epidemiology
Oldenburg, C. E., Moscoe, E., & Bärnighausen, T. (2016) · Current Epidemiology Reports · doi:10.1007/s40471-016-0080-x · Cited by 81
Uttley, J., & Fotios, S. A. (2017) · Accident Analysis & Prevention · doi:10.1016/j.aap.2017.09.005 · Cited by 79
Spatial Causality: A Systematic Review on Spatial Causal Inference
Akbari, K., Winter, S., & Tomko, M. (2021) · Geographical Analysis · doi:10.1111/gean.12312 · Cited by 86
The Minimum Legal Drinking Age and Crime
Carpenter, C. S., & Dobkin, C. (2014) · The Review of Economics and Statistics · doi:10.1162/rest_a_00489 · Cited by 77
Quasi-experimental study designs series—paper 1: introduction: two historical lineages
Bärnighausen, T., Røttingen, J., Rockers, P. C., Shemilt, I., & Tugwell, P. (2017) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2017.02.020 · Cited by 76
Special issue editors’ introduction: The regression discontinuity design—Theory and applications
Imbens, G. W., & Lemieux, T. (2007) · Journal of Econometrics · doi:10.1016/j.jeconom.2007.05.008 · Cited by 77
Randomisation and Its Discontents
Harrison, G. W. (2011) · Journal of African Economies · doi:10.1093/jae/ejr030 · Cited by 76
The minute-scale dynamics of online emotions reveal the effects of affect labeling
Fan, R., Varol, O., Varamesh, A., Barron, A. T. J., van de Leemput, I. A., Scheffer, M., & Bollen, J. (2018) · Nature Human Behaviour · doi:10.1038/s41562-018-0490-5 · Cited by 97
Program Applicants as a Comparison Group in Evaluating Training Programs: Theory and a Test
Bell, S. H., Orr, L. L., Blomquist, J. D., & Cain, G. G. (1995) · Upjohn Research (W.E. Upjohn Institute for Employment Research) · doi:10.17848/9780585284545 · Cited by 73
Evaluating the impact of innovation incentives: evidence from an unexpected shortage of funds
de Blasio, G., Fantino, D., & Pellegrini, G. (2014) · Industrial and Corporate Change · doi:10.1093/icc/dtu027 · Cited by 75
Regression Discontinuity Designs
Hill, R. C. (2017) · Emerald Group Publishing Limited eBooks · doi:10.1108/s0731-9053201738 · Cited by 77
Querubín, P., & Snyder, J. M. (2013) · Quarterly Journal of Political Science · doi:10.1561/100.00012104 · Cited by 72
Observing the Counterfactual? The Search for Political Experiments in Nature
Robinson, G., McNulty, J. E., & Krasno, J. S. (2009) · Political Analysis · doi:10.1093/pan/mpp011 · Cited by 73
Bor, J. H., Fox, M. P., Rosen, S. B., Venkataramani, A. S., Tanser, F. C., Pillay, D., & Bärnighausen, T. (2017) · PLoS Medicine · doi:10.1371/journal.pmed.1002463 · Cited by 72
Evaluating the labor-market effects of compulsory military service
Bauer, T., Bender, S., Paloyo, A. R., & Schmidt, C. Μ. (2012) · European Economic Review · doi:10.1016/j.euroecorev.2012.02.002 · Cited by 72
The effects of access to health insurance: Evidence from a regression discontinuity design in Peru
Bernal, N., Carpio, M. Á., & Klein, T. J. (2017) · Journal of Public Economics · doi:10.1016/j.jpubeco.2017.08.008 · Cited by 96
Examining Prison Effects on Recidivism: A Regression Discontinuity Approach
Mitchell, O., Cochran, J. C., Mears, D. P., & Bales, W. D. (2016) · Justice Quarterly · doi:10.1080/07418825.2016.1219762 · Cited by 71
The effect of schooling on teenage childbearing: evidence using changes in compulsory education laws
Silles, M. A. (2010) · Journal of Population Economics · doi:10.1007/s00148-010-0334-8 · Cited by 70
Eggers, A. C. (2014) · Comparative Political Studies · doi:10.1177/0010414014534199 · Cited by 70
Ferrara, A. R., McCann, P., Pellegrini, G., Stelder, D., & Terribile, F. (2016) · Papers of the Regional Science Association · doi:10.1111/pirs.12234 · Cited by 70
Metadata
- Authors
- Thistlethwaite, D. L., & Campbell, D. T.
- Affiliations
- Northwestern University (US)
- Venue
- Journal of Educational Psychology
- Published
- 1960-12
- Volume
- 51
- Issue
- 6
- Pages
- 309-317
- ISSN
- 0022-0663 (ISSN-L)
- 1939-2176
- OpenAlex
- W2141019942
- Cited by
- 1,469
- References
- 9
- Citations by year
- 2026: 44 · 2025: 59 · 2024: 86 · 2023: 65 · 2022: 104 · 2021: 100 · 2020: 137 · 2019: 85 · 2018: 72 · 2017: 82 · 2016: 75 · 2015: 84 · 2014: 85 · 2013: 56 · 2012: 52
- FWCI
- 1.55
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Educational Psychology (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Education › Educational Research and Methods
- Social Sciences › Education › School Choice and Performance
- Keywords
- causal inference, non-random assignment, academic performance
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review