The DOI matches its Crossref record; 49 of the 51 references it cites were found in a registry or an index.
Using Propensity Scores to Help Design Observational Studies: Application to the Tobacco Litigation
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“Nearly all analyses show Rubin's B<25%, Rubin's R of 0.5–2, and a percentage bias of <10% for each covariate (Fig. 1) (Morgan, 2018; Rubin, 2001).”
From Longitudinal associations between reading for pleasure and child maladjustment: Results from a propensity score matching analysis (2020) · cites this paper as Rubin, 2001
In the citing paper
“We used directed acyclic graphs to identify factors that could be associated with both reading for pleasure and children's strengths and difficulties, or with children's strengths and difficulties only based on previous empirical research (Brookhart et al., 2006; Caliendo and Kopeinig, 2008; Rubin, 2001; Sauer and VanderWeele, 2013).”
From Longitudinal associations between reading for pleasure and child maladjustment: Results from a propensity score matching analysis (2020) · cites this paper as Rubin, 2001
In the citing paper
“Secondly, this process of variable selection can be based on previous research [59].”
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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
Self-citationRosenbaum, P. R., & Rubin, D. B. (1985) · The American Statistician · doi:10.2307/2683903 · Cited by 6,472
Self-citation(1976) · Annals of Economic and Social Measurement · Cited by 5,035
A generalization of sampling without replacement from a finite universe
Horvitz, D. G., & Thompson, D. J. (1952) · Journal of the American Statistical Association · doi:10.1080/01621459.1952.10483446 · Cited by 4,293
Reducing Bias in Observational Studies Using Subclassification on the Propensity Score
Rosenbaum, P. R., & Rubin, D. B. (1984) · Journal of the American Statistical Association · doi:10.1080/01621459.1984.10478078 · Cited by 3,082
Self-citationA Generalization of Sampling Without Replacement From a Finite Universe
Horvitz, D. G., & Thompson, D. J. (1952) · Journal of the American Statistical Association · doi:10.2307/2280784 · Cited by 3,011
Causal effects in nonexperimental studies: Reevaluating the evaluation of training programs
Dehejia, R. H., & Wahba, S. (1999) · Journal of the American Statistical Association · doi:10.1080/01621459.1999.10473858 · Cited by 2,395
Card, D., & Krueger, A. B. (2000) · American Economic Review · doi:10.1257/aer.90.5.1397 · Cited by 2,228
Minimum Wages and Employment: A Case Study of the Fast Food Industry in New Jersey and Pennsylvania
Card, D., & Krueger, A. B. (1993) · National Bureau of Economic Research · doi:10.3386/w4509 · Cited by 2,072
The role of the propensity score in estimating dose-response functions
Imbens, G. W. (2000) · Biometrika · doi:10.1093/biomet/87.3.706 · Cited by 1,779
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Research works printed but not linked: 10
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Trani, J., Pitzer, K., Escallon, J. V., & Bakhshi, P. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19106341 · Cited by 14
“5 and 2 and the percentage bias is below 10% for all covariates (Figures 2 and 3) [64].”
BackgroundDoes grant funding foster research impact? Evidence from France
Corsini, A., & Pezzoni, M. (2023) · Journal of Informetrics · doi:10.1016/j.joi.2023.101448 · Cited by 14
Norton, E. L., Patel, P. M., Levine, D., Wei, J. W., Binongo, J., Leshnower, B. G., Takayama, H., & Chen, E. P. (2023) · European Journal of Cardio-Thoracic Surgery · doi:10.1093/ejcts/ezad231 · Cited by 14
Protected areas are effective on curbing fires in the Amazon
Pessôa, A. C. M., R.S., T. F. M., Silva, C. H. L., Doblas, J., Carvalho, N. S., Aragão, L. E. O. C., & Anderson, L. O. (2023) · Ecological Economics · doi:10.1016/j.ecolecon.2023.107983 · Cited by 14
Mulders, P. J. A. M., van den Heuvel, E. R., van de Molengraft, R., Heemels, W. P. M. H., & Reidsma, P. (2024) · Communications Earth & Environment · doi:10.1038/s43247-024-01658-3 · Cited by 17
“After matching, we evaluated the quality of the matches using three balance measures 50 : (cid:129) Standardized difference of means of the propensity score (should be less than 0.5), (cid:129) Ratio of variance of the propensity scores (should be between 12 and 2), (cid:129) For each background…”
MethodInfluentialGugler, K. P., Szücs, F., & Wohak, U. (2025) · International Journal of Industrial Organization · doi:10.1016/j.ijindorg.2025.103148 · Cited by 14
The Burroughs Wellcome Career Award in the Biomedical Sciences
Pion, G. M., & Cordray, D. S. (2008) · Evaluation & the Health Professions · doi:10.1177/0163278708324434 · Cited by 14
“Most often, it is used in studies for which random assignment is not feasible or has not been used (Dehejia & Wahba, 2002; Rosenthal & Rubin, 1984; Rubin, 2001; Rubin & Thomas, 1996).”
BackgroundMethodA comparison of marginal odds ratio estimators
Loux, T. M., Drake, C., & Smith‐Gagen, J. (2014) · Statistical Methods in Medical Research · doi:10.1177/0962280214541995 · Cited by 14
Casucci, S., Lin, L., Hewner, S. J., & Nikolaev, A. G. (2017) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocx141 · Cited by 14
Hai, A. H. (2019) · Substance Use & Misuse · doi:10.1080/10826084.2018.1555598 · Cited by 14
“…research and scientific understanding suggesting that these factors may be associated either with both the independent variable (i.e., religiosity) and the dependent variables (i.e., alcohol use and/or binge drinking) or with the dependent variables only (Brookhart et al., 2006; Rubin, 2001).”
BackgroundInfluentialImproving boys' reading comprehension with readers theatre
Young, C., Mohr, K. A. J., & Landreth, S. (2020) · Journal of Research in Reading · doi:10.1111/1467-9817.12307 · Cited by 20
Ogawa, T., Seki, K., Tachibana, T., Hayashi, H., Moross, J., Kristensen, M. T., & Shirasawa, S. (2021) · Injury · doi:10.1016/j.injury.2021.07.028 · Cited by 14
Postoperative Radiation Therapy in Oral Cavity Verrucous Carcinoma
Naik, A. N., Silverman, D. A., Rygalski, C. J., Zhao, S., Brock, G. N., Chen, L., Puram, S. V., Rocco, J. W., Baliga, S., VanKoevering, K. K., et al. (2022) · The Laryngoscope · doi:10.1002/lary.30009 · Cited by 14
“25.(19,20) Kaplan–Meier (KM) survival curves were then estimated based on the propensity score matched sample.”
MethodPlant different, eat different? Insights from participatory agricultural research
Azzarri, C., Haile, B., & Letta, M. (2022) · PLoS ONE · doi:10.1371/journal.pone.0265947 · Cited by 14
“While the conditional mean independence assumption for matching is inherently untestable, we assess matching quality based on Rubin’s bias (B) and ratio of variance (R) [56] and propensity score distributions before and after matching using box plots and density function.”
MethodCloney, M. B., Thirunavu, V. M., Roumeliotis, A., Azad, H., Shlobin, N. A., Swong, K. N., Tecle, N. E. E., & Dahdaleh, N. S. (2023) · Neurosurgery · doi:10.1227/neu.0000000000002557 · Cited by 14
Kramer, S. L., Cai, J., & Merlino, F. J. (2015) · Springer eBooks · doi:10.1007/978-3-319-07716-1_2 · Cited by 14
How Do Propensity Score Methods Measure Up in the Presence of Measurement Error? A Monte Carlo Study
de Gil, P. R., Bellara, A. P., Lanehart, R. E., Lee, R. S., Kim, E., & Kromrey, J. D. (2015) · Multivariate Behavioral Research · doi:10.1080/00273171.2015.1022643 · Cited by 14
“Across various disciplines, methodological studies have examined the conditions under which different PSM are able to adequately estimate treatment effects (e.g. Austin, 2009; Austin, Grootendorst, Normand, & Anderson, 2007; Michalopolous, Bloom, & Hill, 2004; Rubin, 2001; Steiner, Cook, Shadish, & Clark, 2010).”
BackgroundDupuytren disease is highly prevalent in male field hockey players aged over 60 years
Broekstra, D. C., van den Heuvel, E. R., Lanting, R., Harder, T., Smits, I., & Werker, P. M. N. (2016) · British Journal of Sports Medicine · doi:10.1136/bjsports-2016-096236 · Cited by 14
The Association between Frailty and Uncorrected Refractive Error in Older Adults
Lee, M. J., Varadaraj, V., Tian, J., Bandeen‐Roche, K., & Swenor, B. K. (2020) · Ophthalmic Epidemiology · doi:10.1080/09286586.2020.1716380 · Cited by 14
“the imbalance of potential confounders (particularly age) in individuals with and without uncorrected refractive error.(22) These propensity scores estimated the probability of an individual having uncorrected”
BackgroundDigoxin Initiation and Outcomes in Patients with Heart Failure with Preserved Ejection Fraction
Lam, P. H., Packer, M., Gill, G. S., Wu, W.-C., Levy, W. C., Zile, M. R., Brar, V., Arundel, C., Cheng, Y., Singh, S. N., et al. (2020) · The American Journal of Medicine · doi:10.1016/j.amjmed.2020.02.040 · Cited by 14
Drug‐eluting stents versus bare metal stents prior to noncardiac surgery
Bangalore, S., Silbaugh, T. S., Normand, S. T., Lovett, A. F., Welt, F. G. P., & Resnic, F. S. (2014) · Catheterization and Cardiovascular Interventions · doi:10.1002/ccd.25617 · Cited by 14
“The PS is the conditional probability of having a particular exposure (DES usage) given a set of measured baseline covariates [15,16].”
BackgroundLudwig, M., Kraus, L., Müller, S., Braun, B., & Bühringer, G. (2012) · Journal of Behavioral Addictions · doi:10.1556/jba.1.2012.4.2 · Cited by 14
“…year 2009) and control subjects (survey year 2006) were matched one-to-one using Mahalanobis metric matching technique including the propensity score within propensity score calipers (Rosenbaum & Rubin, 1985) with a caliper width of 0.2 of a linear propensity score standard deviation (Rubin, 2001).”
MethodInfluentialHow valid can data fusion bePreprint
Kiesl, H., & Rässler, S. (2006) · RePEc: Research Papers in Economics · Cited by 14
Obi, C. T. (2021) · World Bank, Washington, DC eBooks · doi:10.1596/1813-9450-9533 · Cited by 14
“Rubin (2011) also proposes other ways of testing the quality of the matching.”
BackgroundUnnikrishnan, V., Pinet, M., Marc, L. M., Boateng, N. A., Boateng, E. S., Pasanen, T., Mensah, M. A., & Bridonneau, S. (2022) · World Development · doi:10.1016/j.worlddev.2021.105732 · Cited by 13
Freeman, J., & Kirksey, J. J. (2022) · Exceptional Children · doi:10.1177/00144029221108402 · Cited by 15
“Additionally, following recommendations from Rubin (2001), we also refined our selection of covariates based on our conceptual and empirical understanding of how certain background characteristics may influence the probability of receiving an IEP.”
MethodCastro-Toledo, F. J., Llinares, F. M., & Aguerri, J. C. (2023) · Criminal Law Forum · doi:10.1007/s10609-023-09454-y · Cited by 15
“Influential authors such as Judea Pearl (2009, 2010; Pearl and Verma 1995; Pearl Glymour and Jewell 2016), Donald Rubin (2001, 2005) and James Robins (Robins et al. 2000) have driven recent advances in causal analysis emphasizing some of the paradigmatic shifts that the move from traditional…”
BackgroundDalal, R. S., Sharma, P. P., Bains, K., Pruce, J. C., & Allegretti, J. R. (2023) · Inflammatory Bowel Diseases · doi:10.1093/ibd/izad087 · Cited by 13
Ran, G., Wang, G., Du, H., & Lv, M. (2023) · Sustainability · doi:10.3390/su15118900 · Cited by 13
“[40] reported that if the absolute value of the standard deviation of each variable after matching is less than 20%, the matching is good.”
BackgroundParametric and nonparametric propensity score estimation in multilevel observational studies
Salditt, M., & Nestler, S. (2023) · Statistics in Medicine · doi:10.1002/sim.9852 · Cited by 13
Overlap, matching, or entropy weights: what are we weighting for?
Matsouaka, R., Liu, Y., & Zhou, Y. (2024) · Communications in Statistics - Simulation and Computation · doi:10.1080/03610918.2024.2319419 · Cited by 13
“The results, presented in Table 1, indicate the the variances of PSs of the treated to the control groups are similar ( r 2 ½ 0 : 5, 2 � ), per the rule of thumb of Rubin (2001).”
Hernández, C., Herranz, C., Baltaxe, E., Seijas, N., González, R., Asenjo, M. A., Coloma, E., Fernandez, J., Vela, E., Carot-Sans, G., et al. (2024) · Cost Effectiveness and Resource Allocation · doi:10.1186/s12962-024-00536-1 · Cited by 13
“The matching was assessed by the Mahalanobis distance, Rubin’s B (the absolute standardized difference of the means of the linear index of the propensity score in the HaH-HA and Controls) and Rubin’s R [30] (the ratio of HaH-HA to Controls variances of the propensity score index) metrics.”
MethodKarim, M. E. (2024) · The American Statistician · doi:10.1080/00031305.2024.2368794 · Cited by 14
Early identification of rheumatoid arthritis: does it induce treatment-related cost savings?
van Mulligen, E., Mölken, M. R., & Mil, A. H. M. V. D. H. (2024) · Annals of the Rheumatic Diseases · doi:10.1136/ard-2024-225746 · Cited by 13
“22 23 In this study, propensity scores were defined as the conditional probability of being in the early or late group given a set of observed baseline variables.”
Giamouzis, G., Agha, S. A., Ekundayo, O. J., Aban, I., Love, T. E., Daniel, C., Butler, J., & Ahmed, A. (2008) · International Journal of Cardiology · doi:10.1016/j.ijcard.2008.10.049 · Cited by 13
Ripple Effects from Industry Defaults
Bams, D., Pisa, M., & Wolff, C. C. P. (2013) · Small Business Economics · doi:10.1007/s11187-019-00308-9 · Cited by 17
“Moreover, Stuart (2010) and Rubin (2001) discuss a strategy in matching estimators that considers a small set of covariates related to the dependent variable (in our case, small business default rate).”
Input Trade Liberalization and the Export Duration of Products: Evidence from China
Zhou, D., Yang, J., & Lai, M. (2019) · China & World Economy · doi:10.1111/cwe.12305 · Cited by 14
“Following Rubin (2001), we set the caliper to 0.25 times the standard deviation of the propensity score.”
MethodInfluentialAgricultural Mechanization in Nepal—Patterns, Impacts, and Enabling Strategies for Promotion
Takeshima, H., & Bhattarai, M. (2019) · Springer eBooks · doi:10.1007/978-981-32-9648-0_10 · Cited by 13
de Mesquita, P. J. B., Nguyen‐Van‐Tam, J. S., Killingley, B., Enstone, J. E., Lambkin‐Williams, R., Gilbert, A. S., Mann, A., Forni, J., Yan, J., Pantelic, J., et al. (2020) · Influenza and Other Respiratory Viruses · doi:10.1111/irv.12790 · Cited by 13
“of positive samples (%) 6 (7) 14 (17) 66 (45) 111 (76) 2E-10 7E-19”
A Two-Generation Education Intervention and Children’s Attendance in Head Start
Sommer, T. E., Schneider, W., Chor, E., Sabol, T. J., Chase-Lansdale, P. L., Jeanne Brooks-gunn, B., Yoshikawa, H., Morris, A. S., & King, C. T. (2020) · Child Development · doi:10.1111/cdev.13397 · Cited by 13
“However, matching strategies do not account for differences between the treatment and comparison groups along unobservable characteristics (Murnane & Willett, 2010; Rubin, 2001).”
Sommer, A., Leray, E., Lee, Y., & Bind, M. (2020) · Statistics in Medicine · doi:10.1002/sim.8843 · Cited by 15
“5-9 For years, Rubin has argued for a design stage 10 and for a conceptual stage, 2,11 which was formulated more explicitly recently by Bind and Rubin.”
BackgroundInfluentialEverybody Dies: Financial Education and Basic Estate Planning
Kim, K. T., & Stebbins, R. (2021) · Journal of Financial Counseling and Planning · doi:10.1891/jfcp-19-00076 · Cited by 14
Innovation and small and medium enterprises’ performance in Cameroon
Ndzana, M., Onomo, C., Mvogo, G. P., & Bedzeme, T. (2021) · Journal of Small Business and Enterprise Development · doi:10.1108/jsbed-06-2020-0188 · Cited by 13
Bottigliengo, D., Lorenzoni, G., Ocagli, H., Martinato, M., Berchialla, P., & Gregori, D. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18136694 · Cited by 13
“25 suggest a considerable amount of imbalance in the distributions of the baseline covariates between the two groups [76,77].”
BackgroundKhan, N. A., Gong, Z., & Shah, A. A. (2021) · Environmental Science and Pollution Research · doi:10.1007/s11356-021-17615-y · Cited by 13
“However, in our case, which deals with cross-sectional data with no counterfactual information, measuring the impact of adaptation by comparing the average yields of adopters and non-adopters of various measures may calculate biased and misleading estimates (Rubin 2001).”
BackgroundZhao, Y.-J., Xing, X., Tian, T., Wang, Q., Liang, S., Wang, Z., Cheung, T. C. C., Su, Z., Tang, Y., Ng, C. H., et al. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-02089-4 · Cited by 14
Kim, H., & Lee, E. (2022) · Healthcare · doi:10.3390/healthcare10112121 · Cited by 13
“After IPTW, the standardized mean differences (SMD) between the treatment group and the controls, and the variance ratios were well within the recommended ranges (Supplementary Table S2) [28].”
Roy, B., Pawar, P. P., Desai, R. V., Fonarow, G. C., Mujib, M. U., Zhang, Y., Feller, M. A., Ovalle, F., Aban, I., Love, T. E., et al. (2011) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2011.07.046 · Cited by 13
The ethics of consulting for the tobacco industry
Rubin, D. B. (2002) · Statistical Methods in Medical Research · doi:10.1191/0962280202sm297ra · Cited by 12
Self-citationRelationship between Stage of Kidney Disease and Incident Heart Failure in Older Adults
Bowling, C. B., Feller, M. A., Mujib, M. U., Pawar, P. P., Zhang, Y., Ekundayo, O. J., Aban, I., Love, T. E., Sanders, P. W., Anker, S. D., et al. (2011) · American Journal of Nephrology · doi:10.1159/000328905 · Cited by 13
“However, baseline data on kidney damage were not available from CHS participants. Because the prevalence of albuminuria among those with eGFR 60–89 ml/min/1.73 m 2 is low [ , ,”
BackgroundInfluentialKelly, R. (2015) · The Gerontologist · doi:10.1093/geront/gnv145 · Cited by 13
“Acceptable balance on a covariate is obtained when the first diagnostic is close to zero (and no more than 0.25 SDs above zero) and the second and third diagnostics are close to 1 (Rubin, 2001).”
BackgroundMethodInfluentialTsai, L. C. (2016) · Violence Against Women · doi:10.1177/1077801216642869 · Cited by 13
“While there is no firm rule to ascertain whether or not one has achieved appropriate balance, the target used in this study was to keep the absolute standardized differences in means less than 0.25 and the variance ratios between 0.5 and 2 (Rubin, 2001; Stuart, 2010).”
MethodInfluentialAdams, N., GIBBONS, K. S., & Tudehope, D. (2017) · Australian and New Zealand Journal of Obstetrics and Gynaecology · doi:10.1111/ajo.12591 · Cited by 13
Rocks, S., Stepney, M., Głogowska, M., Fazel, M. S., & Tsiachristas, A. (2018) · BMJ Open · doi:10.1136/bmjopen-2018-024230 · Cited by 13
The effects of certification on total factor productivity: A propensity score matching approach
Özbuğday, F. C. (2018) · Managerial and Decision Economics · doi:10.1002/mde.2979 · Cited by 13
Zarychta, A., Andersson, K. P., Root, E. D., MENKEN, J. A., & Grillos, T. (2019) · Health Services and Outcomes Research Methodology · doi:10.1007/s10742-019-00201-8 · Cited by 13
“…gained from the aforementioned interviews and participant observation in an effort to model the treatment decision by estimating a propensity score and using it to select a matched set of treated and control units for additional data collection (Rosenbaum and Rubin 1983; Rubin 2001; Fu et al.”
BackgroundMethodFatema, N. (2019) · World Development · doi:10.1016/j.worlddev.2019.104612 · Cited by 12
Political uncertainty and the choice of external audit: international evidence from private firms
Farooq, O., Satt, H., & Fadel, B. E. (2020) · International Journal of Managerial Finance · doi:10.1108/ijmf-07-2020-0384 · Cited by 13
Leverage multiple real-world data sources in single-arm medical device clinical studies
Lu, N. T., Wang, C., Chen, W.-C., Li, H., Song, C., Tiwari, R. C., Xu, Y., & Yue, L. Q. (2021) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543406.2021.1897994 · Cited by 13
“…number of potentially confounding covariates (Austin 2011; D’Agostino and Rubin 2000; Lunceford and Davidian 2004; Rosenbaum and Rubin 1983, 1984; Rubin 1997, 2001, 2007, 2008; Stuart 2010), the propensity score methodology refers to a collection of versatile statistical tools based on the…”
BackgroundMethodPrevalence of Anemia in Pediatric Patients According to Asthma Control: Propensity Score Analysis
Chang, J., Lee, H., Kim, J., & Rhew, K. (2021) · Journal of Asthma and Allergy · doi:10.2147/jaa.s318641 · Cited by 14
Blocking for Sequential Political Experiments
Moore, R. T., & Moore, S. A. (2013) · Political Analysis · doi:10.1093/pan/mpt007 · Cited by 13
Ahmed, A., & Aronow, W. S. (2007) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2007.03.010 · Cited by 13
“…using a non-parsimonious multivariable logistic regression model, adjusting for all available baseline covariates, and incorporating significant two-way interaction terms in the model (Ahmed, et al., 2006b;Ahmed, et al., 2006c;Ahmed, et al., 2006d;Rosenbaum and Rubin, 1983;Rubin, 1997;Rubin, 2001).”
MethodOh, Y. J., Jung, J. Y., Kim, S. S., Chae, K.-S., Rhu, J., & Lee, C. (2017) · BMC Nephrology · doi:10.1186/s12882-017-0481-1 · Cited by 14
Kompetenzentwicklung im Schuljahr nach PISA 2012: Effekte von Klassenwiederholungen
Ehmke, T., Sälzer, C., Pietsch, M., Drechsel, B., & Müller, K. (2017) · Zeitschrift für Erziehungswissenschaft · doi:10.1007/s11618-017-0752-4 · Cited by 14
Ahmed, A., & Ekundayo, O. J. (2008) · Journal of the American Medical Directors Association · doi:10.1016/j.jamda.2008.08.019 · Cited by 13
“Unlike traditional regression-based multivariable risk adjustment, propensity-matched studies can be designed while remaining blinded to study outcomes thus mimicking one key feature of randomized clinical trials (Figure 1).(17) In addition, covariate imbalances before and after study design can be objectively measure…”
MethodSome aspects of propensity score-based estimators for causal inference
Pingel, R. (2014) · KTH Publication Database DiVA (KTH Royal Institute of Technology) · Cited by 13
Goldring, E. B., Clark, M. A., Rubin, M., Rogers, L. K., Grissom, J. A., Gill, B. T., Kautz, T., McCullough, M., Neel, M., & Burnett, A. (2020) · RePEc: Research Papers in Economics · Cited by 13
The Economic Value of User Tracking for PublishersPreprint
Laub, R., Miller, K. M., & Skiera, B. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4251233 · Cited by 15
“When we calculate the standardized mean differences between the treatment and control group of covariates, we find values below or close to 0.25 (Rubin 2001), indicating a balanced data set.”
MethodInfluentialRoberts, B. W., Mohr, N. M., Ablordeppey, E., Drewry, A. M., Ferguson, I. T., Trzeciak, S., Kollef, M. H., & Fuller, B. M. (2017) · Critical Care Medicine · doi:10.1097/ccm.0000000000002918 · Cited by 12
“Blood product administration, n (%) 78 (13) 37 (9) 41 (24) < 0.”
Wang, S., Li, L., Su, C.-H., Yang, Y., Hsu, T., & Hsu, C. (2019) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.1722 · Cited by 12
Pitter, J. G., Moizs, M., Ezer, É. S., Lukács, G., Szigeti, A., Repa, I., Csanádi, M., Mölken, M. R., Islam, M. K., Kaló, Z., et al. (2022) · PLoS ONE · doi:10.1371/journal.pone.0276719 · Cited by 15
“5 and 2 indicate a sufficient overall balance [63].”
BackgroundZhao, Q., Jia, Q., & Chi, T. (2023) · Therapeutic Advances in Gastroenterology · doi:10.1177/17562848231208669 · Cited by 12
Pediatric Gastrointestinal Tract Outcomes During the Postacute Phase of COVID-19
Zhang, D., Stein, R. E., Lu, Y., Zhou, T., Lei, Y., Li, L., Chen, J., Arnold, J., Becich, M. J., Chrischilles, E. A., et al. (2025) · JAMA Network Open · doi:10.1001/jamanetworkopen.2024.58366 · Cited by 9
Kim, S. H., Lee, H. J., Kim, M. J., Kang, M. G., Kim, J. S., Jang, J. G., Kim, Y., Koo, H., Rhee, C. K., Min, K. H., et al. (2025) · Tuberculosis & respiratory diseases · doi:10.4046/trd.2024.0182 · Cited by 12
Renin Angiotensin Inhibition and Lower Risk of Kidney Failure in Patients with Heart Failure
Patel, S. S., Raman, V. K., Zhang, S., Sheriff, H. M., Fonarow, G. C., Heidenreich, P. A., Faselis, C. J., Lam, P. H., Morgan, C. J., Moore, H., et al. (2025) · The American Journal of Medicine · doi:10.1016/j.amjmed.2025.04.038 · Cited by 14
Arıkan, S., van de Vijver, F. J. R., & Yağmur, K. (2020) · European Journal of Psychology of Education · doi:10.1007/s10212-019-00456-2 · Cited by 16
Prifti, E., Daidone, S., Pace, N., & Davis, B. (2019) · European Review of Agricultural Economics · doi:10.1093/erae/jbz050 · Cited by 12
Return on investment of the diabetes foot care clinical pathway implementation in Alberta, Canada
Thành, N. X., Dmytruk, K., O’Connell, P., Rogers, E., Fillier, D., MacRae, J. M., Thomas, C. M., Rennie, C., Eitzenberger, C., Newman, C., et al. (2020) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2020.108241 · Cited by 12
Peng, S., & Lu, J. (2020) · Public Performance & Management Review · doi:10.1080/15309576.2020.1798788 · Cited by 15
Koyama, Y., Fujiwara, T., Isumi, A., & Doi, S. K. (2020) · BMC Public Health · doi:10.1186/s12889-020-09367-0 · Cited by 15
“Propensity score matching allows to exclude bias regarding exposure allocation before accessing outcome, which makes observational study more analogous to experimental design, and to include as much covariates as possible regardless of sample size [57, 58].”
Do people walk more in transit-accessible places?
Choi, Y., & Guhathakurta, S. (2020) · Journal of Transport and Land Use · doi:10.5198/jtlu.2020.1530 · Cited by 13
Ogawa, T., Yoshii, T., Okawa, A., Fushimi, K., & Jinno, T. (2021) · Clinical Interventions in Aging · doi:10.2147/cia.s315090 · Cited by 12
“A propensity-score is the conditional probability of receiving a specific intervention such as cemented or cementless hemiarthroplasty on a set of measured baseline covariates.(14,15) The propensity-score was estimated using a multivariable logistic regression analysis, calculating the probability of receiving cemente…”
MethodBoard change and firm risk: Do new directors mean unstable corporate policies?
Feng, H., & Xiao, J. Z. (2021) · Corporate Governance An International Review · doi:10.1111/corg.12399 · Cited by 12
Cai, Z., Li, S., Du, G., & Xue, R. (2021) · Sustainability · doi:10.3390/su14010038 · Cited by 11
Liu, Y., Lü, B., Foster, R., Zhang, Y., Zhong, Z. J., Chen, M., & Sun, P. (2022) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543406.2021.2011900 · Cited by 12
Are Residential Energy Efficiency Upgrades Effective? An Empirical Analysis in Southern California
Chuang, Y., Delmas, M. A., & Pincetl, S. (2022) · Journal of the Association of Environmental and Resource Economists · doi:10.1086/718529 · Cited by 12
The Role and Influence of Exclusively Online Degree Programs in Higher Education
Ortagus, J. C., Hughes, R., & Allchin, H. (2024) · American Educational Research Journal · doi:10.3102/00028312231222264 · Cited by 12
“In addition, we employed a covariate balancing approach using standardized mean differences and variance ratios in alignment with recommendations by Shadish et al. (2008) and Rubin (2001).”
MethodComparing treatments via the propensity score: stratification or modeling?
Myers, J. A., & Louis, T. A. (2012) · Health Services and Outcomes Research Methodology · doi:10.1007/s10742-012-0080-3 · Cited by 12
“The lack of necessary user choice in GAMs allowed the outcomes to stay ‘‘hidden’’ until the final step of analysis (except for choosing variables to enter the PS model), as advocated by Rubin (2001, 2007).”
Race and the Natural History of Chronic Heart Failure: A Propensity-Matched Study
Gambassi, G., Agha, S. A., Sui, X., Yancy, C. W., Butler, J., Giamouzis, G., Love, T. E., & Ahmed, A. (2008) · Journal of Cardiac Failure · doi:10.1016/j.cardfail.2008.02.004 · Cited by 12
Zhang, Y., Fonarow, G. C., Sanders, P. W., Farahmand, F., Allman, R. M., Aban, I., Love, T. E., Levesque, R., Kilgore, M. L., & Ahmed, A. (2011) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2011.06.066 · Cited by 12
Does Local Development Influence Outmigration Decisions? Evidence from Indonesia
Tiwari, S. (2017) · World Development · doi:10.1016/j.worlddev.2016.12.028 · Cited by 12
Spatial barriers impact upon appropriate delivery of radiotherapy in breast cancer patients
Stracci, F., Bianconi, F., Lupi, C., Margaritelli, M., Gili, A., & Aristei, C. (2018) · Cancer Medicine · doi:10.1002/cam4.1304 · Cited by 12
“Rubin’s tests and the sensitivity analysis assessed the results of propensity score matching [31, 32].”
MethodThe long-term consequences of youth housing for childbearing and higher education
Öst, C. E., & Wilhelmsson, M. (2019) · Journal of Policy Modeling · doi:10.1016/j.jpolmod.2019.05.008 · Cited by 10
“For a sample to be considered sufficiently balanced, Rubin (2001) recommends that Rubin’s B, i.e., the absolute standardized difference of the mean linear index, of the propensity score between the treated and (matched) control groups, be less than 25 and that Rubin’s R, i.e., the ratio of the…”
BackgroundDirty hands on troubled waters: Sanitation, access to water and child health in Ethiopia
Manalew, W. S., & Tennekoon, V. (2019) · Review of Development Economics · doi:10.1111/rode.12604 · Cited by 12
“…a good balance, the B statistic, the standardized mean difference of the propensity scores in treated and control groups, should be closer to zero and the R statistic, i.e. the variance ratio of propensity scores of treated and untreated (control) observations, should be closer to 1 (Rubin, 2001).”
Singh, T. P., Wong, S. A., Quigley, F., Jenkins, J. S., & Golledge, J. (2020) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2020.08.029 · Cited by 12
How Does Undergraduate Debt Affect Graduate School Application and Enrollment?
Chen, R., & Bahr, P. R. (2020) · Research in Higher Education · doi:10.1007/s11162-020-09610-y · Cited by 12
“Results (available upon request) demonstrated an acceptable level of balance, with absolute standardized differences in means consistently less than 0.25, as recommended by Rubin (2001).”
BackgroundInfluentialThe association between union membership and perceptions of safety climate among US adult workers
Lê, A. B., Wong, S., Lin, H., & Smith, T. D. (2020) · Safety Science · doi:10.1016/j.ssci.2020.105024 · Cited by 12
“Historically, unions and employers have frequently had adversarial relationship due *Rubin (2001) recommends that B be less than 25 and that R be between 0.5 and 2 for the samples to be considered sufficiently balanced.”
BackgroundInfluentialDobson, K. G., Vigod, S. N., Mustard, C., & Smith, P. M. (2021) · Journal of Affective Disorders · doi:10.1016/j.jad.2021.02.019 · Cited by 12
Ogawa, T., Jinno, T., Moriwaki, M., Yoshii, T., Nazarian, A., Fushimi, K., & Okawa, A. (2021) · Injury · doi:10.1016/j.injury.2021.02.092 · Cited by 12
Du, X., Сун, Л., Duivesteijn, W., Nikolaev, A. G., & Pechenizkiy, M. (2019) · TU/e Research Portal · Cited by 12
Metadata
- Authors
- Rubin, D. B.
- Affiliations
- Harvard University (US)
- Corresponding author
- Rubin, Donald B.
- ORCID
- Rubin, Donald B.
- Venue
- Health Services and Outcomes Research Methodology
- Published
- 2001-12
- Volume
- 2
- Issue
- 3-4
- Pages
- 169-188
- ISSN
- 1387-3741 (ISSN-L)
- 1572-9400
- OpenAlex
- W2597503617
- Cited by
- 2,228
- References
- 51
- Citations by year
- 2026: 174 · 2025: 193 · 2024: 196 · 2023: 175 · 2022: 172 · 2021: 166 · 2020: 173 · 2019: 163 · 2018: 123 · 2017: 100 · 2016: 93 · 2015: 75 · 2014: 77 · 2013: 72 · 2012: 44
- FWCI
- 4.04
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Health Services and Outcomes Research Methodology (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- propensity score, observational study design, covariate balance, matching, subclassification, weighting, diagnostic tables, treatment effect estimation, tobacco litigation, National Medical Expenditure Survey, causal inference
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