Design of Observational Studies
Integrity signals
Registry
Cites
Statistics
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?
The propensity score has a balancing property: if customers have the same propensity score, then the difference in their risk characteristics is independent of the assigned treatment.
“Interestingly, this score has a balancing property that states that if customers have the same propensity score, then the difference in their risk characteristics is independent of the assigned treatment, or 𝑇 𝑖 ⟂ 𝑿 𝑖 |𝜋(𝑡 𝑐 , 𝑿 𝑖 ) ∀𝑐 ∈ {1, … , 𝐶} (Guo & Fraser, 2009;Imbens, 2004;Rosenbaum, 2010).”
From Customer price sensitivities in competitive insurance markets (2022) · cites this paper as Rosenbaum, 2010
Quasi-experimental methods such as instrumental variables and regression discontinuity designs allow for causal conclusions from observational snapshots when investigators make strong, explicit assumptions and articulate a credible identification strategy.
“We recognize, of course, that quasi-experimental methods such as instrumental variables and regression discontinuity designs allow for causal conclusions to be drawn from observational snapshots when investigators make strong, explicit assumptions and articulate a credible identification strategy 27-30 .”
From Quantifying the prevalence and impact of overreaching causal claims in social science (2026) · cites this paper as [27]
Cites
The Bias Due to Incomplete Matching
Rosenbaum, P. R., & Rubin, D. B. (1985) · Biometrics · doi:10.2307/2530647 · Cited by 524 · see citing works
Self-citationDoes Cardiac Transplantation Prolong Life?
Gail, M. H. (1972) · Annals of Internal Medicine · doi:10.7326/0003-4819-76-5-815 · Cited by 124 · see citing works
Causal Inference in Randomized Experiments
Rosenbaum, P. R. (2009) · Springer series in statistics · doi:10.1007/978-1-4419-1213-8_2 · Cited by 10 · see citing works
Self-citationCompeting Theories Structure Design
Rosenbaum, P. R. (2009) · Springer series in statistics · doi:10.1007/978-1-4419-1213-8_4 · Cited by 4 · see citing works
Self-citationTwo Simple Models for Observational Studies
Rosenbaum, P. R. (2009) · Springer series in statistics · doi:10.1007/978-1-4419-1213-8_3 · Cited by 3 · see citing works
Self-citationUncommon but Dramatic Responses to Treatment
Rosenbaum, P. R. (2009) · Springer series in statistics · doi:10.1007/978-1-4419-1213-8_16 · Cited by 2 · see citing works
Self-citationRosenbaum, P. R. (1995) · Springer series in statistics · doi:10.1007/978-1-4757-2443-1_7 · Cited by 2 · see citing works
Self-citationCausal Inference in Randomized Experiments
Rosenbaum, P. R. (2021) · Chapman & Hall/CRC eBooks · doi:10.1201/9781003039648-ch1 · Cited by 2 · see citing works
Self-citationInternal and External Validity
(2020) · doi:10.4135/9781529692730 · Cited by 2 · see citing works
(2008) · Apress eBooks · doi:10.1007/978-1-4302-0523-4_18 · Cited by 1 · see citing works
Two Simple Models for Observational Studies
Rosenbaum, P. R. (2020) · Springer series in statistics · doi:10.1007/978-3-030-46405-9_3 · Cited by 1 · see citing works
Self-citationUncommon but Dramatic Responses to Treatment
Rosenbaum, P. R. (2020) · Springer series in statistics · doi:10.1007/978-3-030-46405-9_17 · Cited by 1 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Austin, P. C. (2011) · Multivariate Behavioral Research · doi:10.1080/00273171.2011.568786 · Cited by 12,242 · see citing works
Sensitivity analysis in observational research: Introducing the E-value
VanderWeele, T. J., & Ding, P. (2017) · Annals of Internal Medicine · doi:10.7326/m16-2607 · Cited by 6,350 · see citing works
Matching Methods for Causal Inference: A Review and a Look Forward
Stuart, E. A. (2010) · Statistical Science · doi:10.1214/09-sts313 · Cited by 5,478 · see citing works
Austin, P. C., & Stuart, E. A. (2015) · Statistics in Medicine · doi:10.1002/sim.6607 · Cited by 4,495 · see citing works
Austin, P. (2013) · Statistics in Medicine · doi:10.1002/sim.5984 · Cited by 1,357 · see citing works
Environmental Policy and Directed Technological Change: Evidence from the European Carbon Market
Calel, R., & Dechezleprêtre, A. (2016) · Review of Economics and Statistics · doi:10.1162/rest_a_00470 · Cited by 1,147 · see citing works
Making sense of sensitivity: extending omitted variable bias
Cinelli, C., & Hazlett, C. (2020) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/rssb.12348 · Cited by 1,088 · see citing works
Harder, V. S., Stuart, E. A., & Anthony, J. C. (2010) · Psychological Methods · doi:10.1037/a0019623 · Cited by 802 · see citing works
Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction
Imbens, G. W., & Rubin, D. B. (2015) · Thammasat University Digital Collections · Cited by 838 · see citing works
Gertler, P., Martínez, S., Prémand, P., Rawlings, L. B., & Vermeersch, C. M. J. (2010) · World Bank, Washington, DC eBooks · doi:10.1596/978-0-8213-8541-8 · Cited by 765 · see citing works
Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries
Olteanu, A., Castillo, C., Diaz, F., & Kıcıman, E. (2019) · Frontiers in Big Data · doi:10.3389/fdata.2019.00013 · Cited by 763 · see citing works
Su, X., Yan, X., & Tsai, C. (2012) · Wiley Interdisciplinary Reviews Computational Statistics · doi:10.1002/wics.1198 · Cited by 660 · see citing works
Agnostic notes on regression adjustments to experimental data: Reexamining Freedman’s critique
Lin, W. T. (2013) · The Annals of Applied Statistics · doi:10.1214/12-aoas583 · Cited by 633 · see citing works
Valid post-selection inference
Berk, R. A., Brown, L., Buja, A., Zhang, K., & Zhao, L. H. (2013) · The Annals of Statistics · doi:10.1214/12-aos1077 · Cited by 617 · see citing works
Low-carbon city pilot and carbon emission efficiency: Quasi-experimental evidence from China
Yu, Y., & Zhang, N. (2021) · Energy Economics · doi:10.1016/j.eneco.2021.105125 · Cited by 605 · see citing works
A Systematic Review of Propensity Score Methods in the Social Sciences
Thoemmes, F. J., & Kim, E. S. (2011) · Multivariate Behavioral Research · doi:10.1080/00273171.2011.540475 · Cited by 577 · see citing works
The Econometrics of Randomized Experiments
Athey, S. C., & Imbens, G. W. (2017) · Handbook of economic field experiments · doi:10.1016/bs.hefe.2016.10.003 · Cited by 561 · see citing works
A Practical Introduction to Regression Discontinuity Designs
Cattaneo, M. D., Idrobo, N., & Titiunik, R. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108684606 · Cited by 563 · see citing works
“The importance of falsification tests and the use of placebo outcomes is generally discussed in the analysis of experiments literature (e.g., Imbens and Rubin, 2015; Rosenbaum, 2002, 2010).”
MethodStuart, E. A., Huskamp, H. A., Duckworth, K. S., Simmons, J. B., Song, Z., Chernew, M. E., & Barry, C. L. (2014) · Health Services and Outcomes Research Methodology · doi:10.1007/s10742-014-0123-z · Cited by 535 · see citing works
Matching Methods in Practice: Three Examples
Imbens, G. W. (2015) · The Journal of Human Resources · doi:10.3368/jhr.50.2.373 · Cited by 473 · see citing works
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 466 · see citing works
Econometric Methods for Program Evaluation
Abadie, A., & Cattaneo, M. D. (2018) · Annual Review of Economics · doi:10.1146/annurev-economics-080217-053402 · Cited by 434 · see citing works
Who Gets a Swiss Passport? A Natural Experiment in Immigrant Discrimination
HAINMUELLER, J., & HANGARTNER, D. (2013) · American Political Science Review · doi:10.1017/s0003055412000494 · Cited by 433 · see citing works
Adams, R., Henry, K. E., Sridharan, A., Soleimani, H., Zhan, A., Rawat, N., Johnson, L., Hager, D. N., Cosgrove, S. E., Markowski, A., et al. (2022) · Nature Medicine · doi:10.1038/s41591-022-01894-0 · Cited by 365 · see citing works
Stable weights that balance covariates for estimation with incomplete outcome data
Zubizarreta, J. R. (2015) · Journal of the American Statistical Association · doi:10.1080/01621459.2015.1023805 · Cited by 369 · see citing works
Juvenile Arrest and Collateral Educational Damage in the Transition to Adulthood
Kirk, D., & Sampson, R. (2012) · Sociologia da educação · doi:10.1177/0038040712448862 · Cited by 380 · see citing works
Cattaneo, M. D., Frandsen, B., & Titiunik, R. (2014) · Journal of Causal Inference · doi:10.1515/jci-2013-0010 · Cited by 350 · see citing works
Content or Community? A Digital Business Strategy for Content Providers in the Social Age1
Oestreicher-Singer, G., & Zalmanson, L. (2013) · MIS Quarterly · doi:10.25300/misq/2013/37.2.12 · Cited by 422 · see citing works
Comparative Effectiveness of Regional versus General Anesthesia for Hip Fracture Surgery in Adults
Neuman, M. D., Silber, J. H., Elkassabany, N. M., Ludwig, J. M., & Fleisher, L. A. (2012) · Anesthesiology · doi:10.1097/aln.0b013e3182545e7c · Cited by 326 · see citing works
Randomization Inference with Stata: A Guide and Software
Heß, S. (2017) · The Stata Journal Promoting communications on statistics and Stata · doi:10.1177/1536867x1701700306 · Cited by 320 · see citing works
Causal Inference in Accounting Research
Gow, I. D., Larcker, D. F., & REISS, P. C. (2016) · Journal of Accounting Research · doi:10.1111/1475-679x.12116 · Cited by 312 · see citing works
Anesthesia Technique, Mortality, and Length of Stay After Hip Fracture Surgery
Neuman, M. D., Rosenbaum, P. R., Ludwig, J. M., Zubizarreta, J. R., & Silber, J. H. (2014) · JAMA · doi:10.1001/jama.2014.6499 · Cited by 306 · see citing works
Self-citationSilber, J. H., Rosenbaum, P. R., Clark, A. S., Giantonio, B. J., Ross, R. N., Teng, Y., Wang, M., Niknam, B. A., Ludwig, J. M., Wang, W., et al. (2013) · JAMA · doi:10.1001/jama.2013.8272 · Cited by 304 · see citing works
Self-citationAdvances in Measuring the Environmental and Social Impacts of Environmental Programs
Ferraro, P. J., & Hanauer, M. M. (2014) · Annual Review of Environment and Resources · doi:10.1146/annurev-environ-101813-013230 · Cited by 356 · see citing works
Kazdin, A. E. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108993647.010 · Cited by 279 · see citing works
Kim, S. J., Wang, R. J.-H., & Malthouse, E. C. (2015) · Journal of Interactive Marketing · doi:10.1016/j.intmar.2015.05.004 · Cited by 260 · see citing works
Regression Discontinuity Designs
Cattaneo, M. D., & Titiunik, R. (2022) · Annual Review of Economics · doi:10.1146/annurev-economics-051520-021409 · Cited by 252 · see citing works
“Schochet (2009) discusses power calculations and optimal sample size selection for experimental design using parametric regression specifications for RD treatment effect estimation.”
InfluentialDemocratization Under the Threat of Revolution: Evidence From the Great Reform Act of 1832
Aidt, T. S., & Franck, R. (2015) · Econometrica · doi:10.3982/ecta11484 · Cited by 240 · see citing works
Causal Inference About the Effects of Interventions From Observational Studies in Medical Journals
Dahabreh, I. J., & Bibbins-Domingo, K. (2024) · JAMA · doi:10.1001/jama.2024.7741 · Cited by 242 · see citing works
Characterizing efforts to reduce consumer demand for wildlife products
Veríssimo, D., & Wan, A. K. Y. (2018) · Conservation Biology · doi:10.1111/cobi.13227 · Cited by 230 · see citing works
“Such observational studies are typically divided between qualitative case studies and quantitative quasi-experiments (Rosenbaum 2010).”
BackgroundInfluentialMatching Methods in Practice: Three Examples
Imbens, G. W. (2014) · National Bureau of Economic Research · doi:10.3386/w19959 · Cited by 229 · see citing works
Chagas, A. L. S., Azzoni, C. R., & de Almeida, A. N. (2016) · Regional Science and Urban Economics · doi:10.1016/j.regsciurbeco.2016.04.002 · Cited by 222 · see citing works
Zubizarreta, J. R. (2012) · Journal of the American Statistical Association · doi:10.1080/01621459.2012.703874 · Cited by 219 · see citing works
Instrumental Variables: An Econometrician's Perspective
Imbens, G. W. (2014) · Statistical Science · doi:10.1214/14-sts480 · Cited by 212 · see citing works
Long-Term Economic Distress, Cultural Backlash, and Support for Brexit
Carreras, M., Carreras, Y. İ., & Bowler, S. (2019) · Comparative Political Studies · doi:10.1177/0010414019830714 · Cited by 216 · see citing works
“The first one is the existence of posttreatment bias (Rosenbaum, 1984, 2010), which refers to adjusting for characteristics that can be affected by exposure to economic decline (e.g., the level of development, migration flows, sociodemographic characteristics, etc.).”
BackgroundWhen Natural Experiments Are Neither Natural nor Experiments
Sekhon, J. S., & Titiunik, R. (2012) · American Political Science Review · doi:10.1017/s0003055411000542 · Cited by 194 · see citing works
Liu, W., Kuramoto, S. J., & Stuart, E. A. (2013) · Prevention Science · doi:10.1007/s11121-012-0339-5 · Cited by 194 · see citing works
A Selective Review of Negative Control Methods in Epidemiology
Shi, X., Miao, W., & Tchetgen, E. T. (2020) · Current Epidemiology Reports · doi:10.1007/s40471-020-00243-4 · Cited by 194 · see citing works
“In prior literature, NCO has been referred to as falsification outcome/end point [23–26], control outcome [14, 27, 28], secondary outcome [29, 30], supplementary response [6] and unaffected outcome [31].”
BackgroundEnvironmental Policy and Directed Technological Change: Evidence from the European Carbon MarketPreprint
Calel, R. A., & Dechezleprêtre, A. (2012) · SSRN Electronic Journal · doi:10.2139/ssrn.2041147 · Cited by 193 · see citing works
Imbens, G. W. (2020) · Journal of Economic Literature · doi:10.1257/jel.20191597 · Cited by 208 · see citing works
Robustness Tests for Quantitative Research
Neumayer, E., & Plümper, T. (2017) · Cambridge University Press eBooks · doi:10.1017/9781108233590 · Cited by 166 · see citing works
Examining gifting behavior on live streaming platforms: An identity-based motivation model
Li, R., Lu, Y., Ma, J., & Wang, W. (2020) · Information & Management · doi:10.1016/j.im.2020.103406 · Cited by 173 · see citing works
LABELING EFFECTS OF FIRST JUVENILE ARRESTS: SECONDARY DEVIANCE AND SECONDARY SANCTIONING
LIBERMAN, A. M., KIRK, D. S., & KIM, K. (2014) · Criminology · doi:10.1111/1745-9125.12039 · Cited by 216 · see citing works
The Statistics of Causal Inference: A View from Political Methodology
Keele, L. J. (2015) · Political Analysis · doi:10.1093/pan/mpv007 · Cited by 169 · see citing works
The Value of Fit Information in Online Retail: Evidence from a Randomized Field Experiment
Gallino, S., & Moreno, A. (2018) · Manufacturing & Service Operations Management · doi:10.1287/msom.2017.0686 · Cited by 158 · see citing works
“15 Alternatively, it is possible to use a randomization test of no effect (Rosenbaum 2010, Chapter 2).”
Building a Stronger Instrument in an Observational Study of Perinatal Care for Premature Infants
Baiocchi, M., Small, D. S., Lorch, S. A., & Rosenbaum, P. R. (2010) · Journal of the American Statistical Association · doi:10.1198/jasa.2010.ap09490 · Cited by 166 · see citing works
Self-citationEffectiveness of Community Forest Management at reducing deforestation in Madagascar
Rasolofoson, R., Ferraro, P. J., Jenkins, C. N., & Jones, J. P. G. (2015) · Biological Conservation · doi:10.1016/j.biocon.2015.01.027 · Cited by 165 · see citing works
Linden, A., Mathur, M. B., & VanderWeele, T. J. (2020) · The Stata Journal Promoting communications on statistics and Stata · doi:10.1177/1536867x20909696 · Cited by 161 · see citing works
Modern Algorithms for Matching in Observational Studies
Rosenbaum, P. R. (2019) · Annual Review of Statistics and Its Application · doi:10.1146/annurev-statistics-031219-041058 · Cited by 157 · see citing works
Self-citationCattaneo, M. D., Titiunik, R., & Vázquez-Baré, G. (2017) · Journal of Policy Analysis and Management · doi:10.1002/pam.21985 · Cited by 155 · see citing works
A practical guide to propensity score analysis for applied clinical research.
Lee, J., & Little, T. (2017) · Behaviour Research and Therapy · doi:10.1016/j.brat.2017.01.005 · Cited by 125 · see citing works
Forastiere, L., Airoldi, E. M., & Mealli, F. (2020) · Journal of the American Statistical Association · doi:10.1080/01621459.2020.1768100 · Cited by 144 · see citing works
“Under SUTVA and if individual covariates form a sufficient set for unconfoudedness, that is, Yi(z) ⊥⊥ Zi|X ∀z = 0, 1, then an unbiased estimator of τ obs X? would provide an unbiased estimate of the average treatment effect τsutva (Rosenbaum, 2010; VanderWeele & Arah, 2011).”
BackgroundOnline Actions with Offline Impact
Althoff, T., Jindal, P., & Leskovec, J. (2017) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/3018661.3018672 · Cited by 143 · see citing works
Childhood Socialization and Political Attitudes: Evidence from a Natural Experiment
Healy, A., & Malhotra, N. A. (2013) · The Journal of Politics · doi:10.1017/s0022381613000996 · Cited by 136 · see citing works
Association of Playing High School Football With Cognition and Mental Health Later in Life
Deshpande, S. K., Hasegawa, R., Rabinowitz, A. R., Whyte, J., Roan, C., Tabatabaei, A., Baiocchi, M., Karlawish, J., Master, C. L., & Small, D. S. (2017) · JAMA Neurology · doi:10.1001/jamaneurol.2017.1317 · Cited by 122 · see citing works
Incarceration, education and transition from delinquency
Blomberg, T. G., Bales, W. D., Mann, K., Piquero, A. R., & Berk, R. A. (2011) · Journal of Criminal Justice · doi:10.1016/j.jcrimjus.2011.04.003 · Cited by 157 · see citing works
Bringing the Person Back In: Boundaries, Perceptions, and the Measurement of Racial Context
Wong, C. J., Bowers, J., Williams, T., & Simmons, K. D. (2012) · The Journal of Politics · doi:10.1017/s0022381612000552 · Cited by 137 · see citing works
When the test of mediation is more powerful than the test of the total effect
O’Rourke, H. P., & MacKinnon, D. P. (2014) · Behavior Research Methods · doi:10.3758/s13428-014-0481-z · Cited by 136 · see citing works
Green, K. M., Doherty, E. E., Stuart, E. A., & Ensminger, M. E. (2010) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2010.05.018 · Cited by 134 · see citing works
Silber, J. H., Rosenbaum, P. R., Ross, R. N., Reiter, J. G., Niknam, B. A., Hill, A. S., Bongiorno, D. M., Shah, S. A., Hochman, L. L., Even‐Shoshan, O., et al. (2018) · Milbank Quarterly · doi:10.1111/1468-0009.12355 · Cited by 136 · see citing works
Self-citationGarabedian, L. F., Chu, P., Toh, S., Zaslavsky, A. M., & Soumerai, S. B. (2014) · Annals of Internal Medicine · doi:10.7326/m13-1887 · Cited by 133 · see citing works
Christie, A. P., Abecasis, D., Adjeroud, M., Alonso, J. C., Amano, T., Antón, Á., Baldigo, B. P., Barrientos, R., Bicknell, J. E., Buhl, D. A., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-20142-y · Cited by 135 · see citing works
Inference in Regression Discontinuity Designs under Local Randomization
Cattaneo, M. D., Titiunik, R., & Vázquez-Baré, G. (2016) · The Stata Journal Promoting communications on statistics and Stata · doi:10.1177/1536867x1601600205 · Cited by 131 · see citing works
Association Between Connecticut’s Permit-to-Purchase Handgun Law and Homicides
Rudolph, K. E., Stuart, E. A., Vernick, J. S., & Webster, D. W. (2015) · American Journal of Public Health · doi:10.2105/ajph.2015.302703 · Cited by 128 · see citing works
Statistical Challenges of Administrative and Transaction Data
Hand, D. J. (2018) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/rssa.12315 · Cited by 129 · see citing works
Kot, F. C. (2014) · Research in Higher Education · doi:10.1007/s11162-013-9325-4
Relaxing Occupational Licensing Requirements: Analyzing Wages and Prices for a Medical Service
Kleiner, M. M., Marier, A., Park, K. W., & Wing, C. (2016) · The Journal of Law and Economics · doi:10.1086/688093 · Cited by 181 · see citing works
Causal Inference: A Missing Data Perspective
Ding, P., & Li, F. (2018) · Statistical Science · doi:10.1214/18-sts645 · Cited by 119 · see citing works
A natural experiment of social network formation and dynamics
Phan, T., & Airoldi, E. (2015) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.1404770112 · Cited by 130 · see citing works
Reasoning about Interference Between Units: A General Framework
Bowers, J., Fredrickson, M., & Panagopoulos, C. (2012) · Political Analysis · doi:10.1093/pan/mps038 · Cited by 124 · see citing works
Yuan, Z., Jiao, F., Shi, X., Sardans, J., Maestre, F. T., Delgado‐Baquerizo, M., Reich, P. B., & Peñuelas, J. (2017) · eLife · doi:10.7554/elife.23255 · Cited by 122 · see citing works
Randomization Inference for Treatment Effect Variation
Ding, P., Feller, A., & Miratrix, L. W. (2015) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/rssb.12124 · Cited by 120 · see citing works
Zubizarreta, J. R., Paredes, R., & Rosenbaum, P. R. (2014) · ScholarlyCommons (University of Pennsylvania) · Cited by 117 · see citing works
Self-citationA 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 · see citing works
Silber, J. H., Rosenbaum, P. R., McHugh, M. D., Ludwig, J. M., Smith, H. L., Niknam, B. A., Even‐Shoshan, O., Fleisher, L. A., Kelz, R. R., & Aiken, L. H. (2016) · JAMA Surgery · doi:10.1001/jamasurg.2015.4908 · Cited by 116 · see citing works
Self-citationLand Use Change Increases Streamflow Across the Arc of Deforestation in Brazil
Levy, M. C., Lopes, A. V., Cohn, A. S., Larsen, L. G., & Thompson, S. (2018) · Geophysical Research Letters · doi:10.1002/2017gl076526 · Cited by 117 · see citing works
Matching Methods for Confounder Adjustment: An Addition to the Epidemiologist’s Toolbox
Greifer, N., & Stuart, E. A. (2021) · Epidemiologic Reviews · doi:10.1093/epirev/mxab003 · Cited by 124 · see citing works
To use or not to use propensity score matching?
Wang, J. (2020) · Pharmaceutical Statistics · doi:10.1002/pst.2051 · Cited by 114 · see citing works
“In fact, similar approaches exist in the toolkit for matching, known as matching with fine balancing.(39,40) These approach match subjects under the constraints of balancing some factors that are important but difficult to match.”
MethodWest, S. G., Cham, H., Thoemmes, F. J., Renneberg, B., Schulze, J., & Weiler, M. (2014) · Journal of Consulting and Clinical Psychology · doi:10.1037/a0036387 · Cited by 113 · see citing works
Zubizarreta, J. R., Paredes, R. D., & Rosenbaum, P. R. (2014) · The Annals of Applied Statistics · doi:10.1214/13-aoas713 · Cited by 111 · see citing works
Self-citationImproving Inter-Laboratory Reproducibility in Measurement of Biochemical Methane Potential (BMP)
Hafner, S. D., de Laclos, H. F., Koch, K., & Holliger, C. (2020) · Water · doi:10.3390/w12061752 · Cited by 109 · see citing works
Acute kidney injury is a risk factor for subsequent proteinuria
Parr, S. K., Matheny, M. E., Abdel-Kader, K. F. M., Greevy, R. A., Bian, A., Fly, J., Chen, G., Speroff, T., Hung, A. M., Ikizler, T. A., et al. (2017) · Kidney International · doi:10.1016/j.kint.2017.07.007 · Cited by 106 · see citing works
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 107 · see citing works
Donor Retention in Online Crowdfunding Communities
Althoff, T., & Leskovec, J. (2015) · International World Wide Web Conference (WWW) · doi:10.1145/2736277.2741120 · Cited by 106 · see citing works
Pimentel, S. D., Kelz, R. R., Silber, J. H., & Rosenbaum, P. R. (2015) · Journal of the American Statistical Association · doi:10.1080/01621459.2014.997879 · Cited by 106 · see citing works
Self-citationOptimal Matching of an Optimally Chosen Subset in Observational Studies
Rosenbaum, P. R. (2011) · Journal of Computational and Graphical Statistics · doi:10.1198/jcgs.2011.09219 · Cited by 104 · see citing works
Self-citationZeyringer, M., Pachauri, S., Schmid, E., Schmidt, J., Worrell, E., & Morawetz, U. B. (2015) · Energy Sustainable Development/Energy for sustainable development · doi:10.1016/j.esd.2015.01.003 · Cited by 101 · see citing works
AI-Aided Teaching Model in Education 5.0
Khang, A., Muthmainnah, M., Seraj, P. M. I., Yakin, A. M. A., & Obaid, A. J. (2023) · Advances in computational intelligence and robotics book series · doi:10.4018/978-1-6684-8851-5.ch004 · Cited by 100 · see citing works
Imbens, G. W. (2019) · National Bureau of Economic Research · doi:10.3386/w26104 · Cited by 101 · see citing works
Economic performance and incumbents' support in Latin America
Murillo, M. V., & Visconti, G. (2016) · Electoral Studies · doi:10.1016/j.electstud.2016.10.007 · Cited by 97 · see citing works
- Authors
- Rosenbaum, P. R.
- Affiliations
- University of Pennsylvania (US)
- Corresponding author
- Rosenbaum, Paul R.
- ORCID
- Rosenbaum, Paul R.
- Venue
- Springer Series in Statistics
- Publisher
- Springer New York
- Published
- 2010
- ISSN
- 0172-7397 (ISSN-L)
- OpenAlex
- W253646976
- Cited by
- 1,150
- References
- 12
- Citations by year
- 2026: 33 · 2025: 72 · 2024: 58 · 2023: 58 · 2022: 73 · 2021: 115 · 2020: 108 · 2019: 71 · 2018: 73 · 2017: 68 · 2016: 75 · 2015: 85 · 2014: 84 · 2013: 58 · 2012: 55
- FWCI
- 6.61
- Type
- book
- Language
- en
- Open access
- closed
- Licence
- Locations
- Springer series in statistics (publishedVersion)
- CERN Document Server (European Organization for Nuclear Research) (submittedVersion)
- Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)) (submittedVersion)
- Funders
- National Science Foundation
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
- Keywords
- observational studies, research design, causal inference, statistical inference, confounding
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