The DOI matches its Crossref record; 42 of the 43 references it cites were found in a registry or an index.
Assessing the Effect of Race Bias in Post-traffic Stop Outcomes Using Propensity Scores
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Citations
Cites
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
(1990) · Choice Reviews Online · doi:10.5860/choice.27-3338 · Cited by 35,305
The central role of the propensity score in observational studies for causal effects
ROSENBAUM, P. R., & RUBIN, D. B. (1983) · Biometrika · doi:10.1093/biomet/70.1.41 · Cited by 31,241
Greedy function approximation: A gradient boosting machine
Friedman, J. H. (2001) · The Annals of Statistics · doi:10.1214/aos/1013203451 · Cited by 30,731
(2001) · RePEc: Research Papers in Economics · Cited by 27,577
The Elements of Statistical Learning
Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162
Classification and Regression Trees.
Gordon, A. D., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984) · Biometrics · doi:10.2307/2530946 · Cited by 23,867
Classification and Regression Trees.
Ryzin, J. V., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1986) · Journal of the American Statistical Association · doi:10.2307/2288003 · Cited by 21,030
(2005) · Springer eBooks · doi:10.1007/0-387-27255-0_9 · Cited by 20,333
Hosmer, D. W., & Lemeshow, S. (2000) · doi:10.1002/0471722146 · Cited by 20,302
McCullagh, P., & Nelder, J. A. (1989) · doi:10.1007/978-1-4899-3242-6 · Cited by 16,836
Classification And Regression Trees
Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (2017) · doi:10.1201/9781315139470 · Cited by 11,417
Classification and regression trees
Praagman, J. (1985) · European Journal of Operational Research · doi:10.1016/0377-2217(85)90321-2 · Cited by 10,053
Estimating causal effects of treatments in randomized and nonrandomized studies
Rubin, D. B. (1974) · Journal of Educational Psychology · doi:10.1037/h0037350 · Cited by 9,436
Unequal treatment: confronting racial and ethnic disparities in health care
(2003) · Choice Reviews Online · doi:10.5860/choice.40-5843 · Cited by 7,043
Unequal treatment: confronting racial and ethnic disparities in health care.
Smedley, B. D., Stith, A. Y., & Nelson, A. (2003) · University Libraries (University of Maryland) · doi:10.13016/1bbm-d7bq · Cited by 6,567
Fisher, R. A. (1936) · BMJ · doi:10.1136/bmj.1.3923.554-a · Cited by 4,980
Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review
Imbens, G. W. (2004) · Review of Economics and Statistics · doi:10.1162/003465304323023651 · Cited by 2,994
Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score
Hirano, K., Imbens, G. W., & Ridder, G. (2003) · Econometrica · doi:10.1111/1468-0262.00442 · Cited by 2,602
Rosenbaum, P. R. (2002) · Springer series in statistics · doi:10.1007/978-1-4757-3692-2 · Cited by 2,543
Bayesian inference for causal effects: The role of randomization
Rubin, D. B. (1978) · The Annals of Statistics · doi:10.1214/aos/1176344064 · Cited by 2,503
Causal Inference Using Potential Outcomes: Design, Modeling, Decisions
Rubin, D. B. (2005) · Journal of the American Statistical Association · doi:10.1198/016214504000001880 · Cited by 2,173
Generalized linear models. 2nd ed.
McCullagh, P., & Nelder, J. (1993) · Journal of the American Statistical Association · doi:10.2307/2290358 · Cited by 1,581
McCaffrey, D. F., Ridgeway, G., & Morral, A. R. (2004) · Psychological Methods · doi:10.1037/1082-989x.9.4.403 · Cited by 1,317
Self-citationHirano, K., & Imbens, G. W. (2001) · Health Services and Outcomes Research Methodology · doi:10.1023/a:1020371312283 · Cited by 1,039
Rosenbaum, P. R. (1987) · Journal of the American Statistical Association · doi:10.1080/01621459.1987.10478441 · Cited by 998
Racial Bias in Motor Vehicle Searches: Theory and Evidence
Knowles, J., Persico, N., & Todd, P. (2001) · Journal of Political Economy · doi:10.1086/318603 · Cited by 608
Statistics and Causal Inference: Comment: Which Ifs Have Causal Answers
Rubin, D. B. (1986) · Journal of the American Statistical Association · doi:10.2307/2289065 · Cited by 517
Nonparametric Estimation of Average Treatment Effects under Exogeneity: A Review
Imbens, G. W. (2003) · National Bureau of Economic Research · doi:10.3386/t0294 · Cited by 460
Rubin, D. B. (1986) · Journal of the American Statistical Association · doi:10.1080/01621459.1986.10478355 · Cited by 289
Testing for Racial Profiling in Traffic Stops From Behind a Veil of Darkness
Grogger, J., & Ridgeway, G. (2006) · Journal of the American Statistical Association · doi:10.1198/016214506000000168 · Cited by 260
Self-citationENGEL, R. S., & Cherkauskas, J. C. (2004) · Justice Quarterly · doi:10.1080/07418820400095741 · Cited by 257
Profiles in injustice: why racial profiling cannot work
(2002) · Choice Reviews Online · doi:10.5860/choice.40-0360 · Cited by 256
Racial Profiling? A Multivariate Analysis of Police Traffic Stop Data
Smith, M. R., & Petrocelli, M. (2001) · Police Quarterly · doi:10.1177/1098611101004001001 · Cited by 198
Controlling Street-Level Police Discretion
Mastrofski, S. D. (2004) · The Annals of the American Academy of Political and Social Science · doi:10.1177/0002716203262584 · Cited by 193
Reducing Gun Violence: Results from an Intervention in East Los Angeles
Tita, G., Riley, K., Ridgeway, G. K., Grammich, C. A., Abrahamse, A., & Greenwood, P. (2003) · RAND Corporation eBooks · doi:10.7249/mr1764 · Cited by 159
Self-citationBerk, R. A., & Newton, P. J. (1985) · American Sociological Review · doi:10.2307/2095413 · Cited by 142
SUSPECT SEARCHES: ASSESSING POLICE BEHAVIOR UNDER THE U.S. CONSTITUTION*
GOULD, J. B., & MASTROFSKI, S. D. (2004) · Criminology & Public Policy · doi:10.1111/j.1745-9133.2004.tb00046.x · Cited by 134
UNCONSTITUTIONAL POLICE SEARCHES AND COLLECTIVE RESPONSIBILITY
Harcourt, B. E. (2004) · Criminology & Public Policy · doi:10.1111/j.1745-9133.2004.tb00047.x · Cited by 84
Alpert, G. P., Smith, M. R., & Dunham, R. G. (2004) · Justice Research and Policy · doi:10.3818/jrp.6.1.2004.43 · Cited by 50
EFFICIENT ESTIMATION OF AVERAGE TREATMENT EFFECTS
Imbens, G. W. (2003) · Cited by 44
Toward New Images of Policing: Herman Goldstein's "Problem-Oriented Policing"
Kelling, G. L. (1992) · Law & Social Inquiry · doi:10.1086/492393 · Cited by 6
Research works printed but not linked: 2
- Ridgeway G. (1999). The state of boosting. Comput. Sci. Stat. 31:172–181
- Rubin D. B. (1986). Which ifs have causal statements? J. Am. Stat. Assoc. 81(396):961–962
Cited by
Sorted by citations
A large-scale analysis of racial disparities in police stops across the United States
Pierson, E., Simoiu, C., Overgoor, J., Corbett-Davies, S., Jenson, D., Shoemaker, A., Ramachandran, V., Barghouty, P., Phillips, C., Shroff, R., et al. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-0858-1 · Cited by 552
Incarceration as Exposure: The Prison, Infectious Disease, and Other Stress-Related Illnesses
Massoglia, M. (2008) · Journal of Health and Social Behavior · doi:10.1177/002214650804900105 · Cited by 474
Administrative Records Mask Racially Biased Policing
KNOX, D., LOWE, W., & MUMMOLO, J. (2020) · American Political Science Review · doi:10.1017/s0003055420000039 · Cited by 314
“…examples represent a mere fraction of a decades-long, multidisciplinary effort to quantify the degree to which police discriminate against civilians of color [see Atiba Goff and Kahn (2012), Fridell (2017), and Ridgeway and MacDonald (2010) for more extensive reviews of this empirical literature].”
A multidisciplinary survey on discrimination analysis
Romei, A., & Ruggieri, S. (2014) · The Knowledge Engineering Review · doi:10.1017/s0269888913000039 · Cited by 288
“The reference work for the propensity score approach can be found in Ridgeway (2006), who adopts risk difference as a discrimination measure, called the race effect, and estimates propensity scores by logistic regression on a data set of the Oakland Police Department.”
BackgroundMethodPrecinct or prejudice? Understanding racial disparities in New York City’s stop-and-frisk policy
Goel, S., Rao, J. M., & Shroff, R. (2016) · The Annals of Applied Statistics · doi:10.1214/15-aoas897 · Cited by 285
“In a novel design, Grogger and Ridgeway (2006) analyzed traffic stops in Oakland and showed that the racial distribution of stopped individuals during the day, when a suspect’s race is readily apparent, matches the distribution at night, when the “veil of darkness” masks race, and thus concluded…”
Background
Metadata
- Authors
- Ridgeway, G.
- Affiliations
- RAND Corporation (US)
- Corresponding author
- Ridgeway, Greg
- ORCID
- Ridgeway, Greg
- Venue
- Journal of Quantitative Criminology
- Published
- 2006-03
- Volume
- 22
- Issue
- 1
- Pages
- 1-29
- ISSN
- 0748-4518 (ISSN-L)
- 1573-7799
- OpenAlex
- W1966721996
- Cited by
- 176
- References
- 43
- Citations by year
- 2026: 5 · 2025: 6 · 2024: 6 · 2023: 8 · 2022: 3 · 2021: 6 · 2020: 13 · 2019: 4 · 2018: 9 · 2017: 8 · 2016: 12 · 2015: 11 · 2014: 14 · 2013: 17 · 2012: 10
- FWCI
- 52.87
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Journal of Quantitative Criminology (publishedVersion)
- Topics
- Social Sciences › Political Science and International Relations › Policing Practices and Perceptions
- Social Sciences › Sociology and Political Science › Criminal Justice and Corrections Analysis
- Social Sciences › Education › Education Discipline and Inequality
- Keywords
- traffic stops, racial bias, police discretion, racial profiling, search, citation, stop duration, Oakland Police Department
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