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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- D. J. Benjamin, “Does 401(k) eligibility increase net national savings?: reducing bias in the eligibility effect estimate,” A. B. Honors Thesis in Economics, Harvard University, Cambridge, MA, 1999.
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Items 501–600 of 1,001
Effect of fertilizer subsidy on household level cereal production in Ghana
Tsiboe, F., Egyir, I. S., & Anaman, G. (2021) · Scientific African · doi:10.1016/j.sciaf.2021.e00916 · Cited by 40
Doherty, E. E., Cwick, J., Green, K. M., & Ensminger, M. E. (2015) · Justice Quarterly · doi:10.1080/07418825.2015.1016089 · Cited by 39
“Controlling for these variables within a conventional regression analysis may not adequately take into account the many ways the two populations are likely to differ (Rubin, 2001).”
BackgroundMethodThe Effect of a Large Regional Health Plan’s Value-based Insurance Design Program on Statin Use
Frank, M. B., Fendrick, A. M., He, Y., Zbrozek, A. S., Holtz, N., Leung, S., & Chernew, M. E. (2012) · Medical Care · doi:10.1097/mlr.0b013e31826c8630 · Cited by 34
“Once weighted, patient characteristics in the treatment and control groups should be similar.(15)”
BackgroundKlatte, T., Fife, K. M., Welsh, S. J., Sachdeva, M., Armitage, J. N., Aho, T., Riddick, A. C. P., Matakidou, A., Eisen, T. G., & Stewart, G. D. (2017) · World Journal of Urology · doi:10.1007/s00345-017-2154-x · Cited by 34
“Of note, the design phase of the study is separated from the analysis phase, which is more comparable to randomised experiments [18].”
Outcome Effects on Recidivism Among Drug Court Participants
Gibbs, B. R., Lytle, R. D., & Wakefield, W. (2018) · Criminal Justice and Behavior · doi:10.1177/0093854818800528 · Cited by 33
Firm productivity and importing: Evidence from Chinese manufacturing firms
Elliott, R., Jabbour, L., & Zhang, L. (2016) · Canadian Journal of Economics/Revue canadienne d économique · doi:10.1111/caje.12226 · Cited by 33
“Rubin (2001) recommends that B be less than 25 and that R be between 0.5 and two for the samples to be considered sufficiently balanced.”
InfluentialEffects of Voluntary Time-of-Use Pricing on Summer Electricity Usage of Business Customers
Qiu, Y. L., Kirkeide, L., & Wang, Y. D. (2016) · Environmental and Resource Economics · doi:10.1007/s10640-016-0084-5 · Cited by 33
Labour Migration, Food Expenditure, and Household Food Security in Eastern Indonesia
Hasanah, A., Mendolia, S., & Yerokhin, O. (2017) · Economic Record · doi:10.1111/1475-4932.12344 · Cited by 33
Spironolactone and Outcomes in Older Patients with Heart Failure and Reduced Ejection Fraction
Bayoumi, E., Lam, P. H., Dooley, D. J., Singh, S. N., Faselis, C. J., Morgan, C. J., Patel, S. S., Sheriff, H. M., Mohammed, S. F., Palant, C. E., et al. (2018) · The American Journal of Medicine · doi:10.1016/j.amjmed.2018.09.011 · Cited by 33
Improving reading comprehension with readers theater
Young, C., Durham, P., Miller, M., Rasinski, T. V., & Lane, F. (2019) · The Journal of Educational Research · doi:10.1080/00220671.2019.1649240 · Cited by 33
“The standardized mean difference between the groups on propensity scores and covariates should not exceed 0.2 (Caliendo & Kopeinig, 2008; Rubin, 2001).”
BackgroundInfluentialBalachandran, T., Cohen, G. H., Foll, B. L., Rehm, J. T., & Hassan, A. N. (2019) · The American Journal of Drug and Alcohol Abuse · doi:10.1080/00952990.2019.1690495 · Cited by 36
“25) and visual diagnostic methods (28,34).”
Cuenca‐Zaldívar, J. N., Calvo, S., Bravo-Esteban, E., Ruiz, P. O., Santi-Cano, M. J., & Herrero, P. (2020) · Acupuncture in Medicine · doi:10.1177/0964528420947426 · Cited by 33
Women in the Inner Circle: Gender and Director Networks After the Fracturing of the Corporate Elite
Benton, R. A. (2021) · Organization Science · doi:10.1287/orsc.2021.1433 · Cited by 33
Mueller, A. M., Liakoni, E., Schneider, C., Burkard, T., Jick, S. S., Krähenbühl, S., Meier, C. R., & Spoendlin, J. (2021) · Journal of General Internal Medicine · doi:10.1007/s11606-021-06651-6 · Cited by 33
Main, J. B., Wang, Y., & Tan, L. (2021) · Journal of Engineering Education · doi:10.1002/jee.20416 · Cited by 39
“20 after our matching procedure, suggesting covariate balance (Linden & Samuels, 2013; Normand et al., 2001; Rubin, 2001).”
MethodInfluentialLu, 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:10.1080/10543406.2021.1998098 · Cited by 36
“…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…”
BackgroundMethodBodendorf, F., Sauter, M., & Franke, J. E. (2022) · International Journal of Production Economics · doi:10.1016/j.ijpe.2022.108708 · Cited by 40
Long-term benefits of full-day kindergarten: a longitudinal population-based study
Brownell, M. D., Nickel, N. C., Chateau, D. G., Martens, P. J., Taylor, C. R., Crockett, L. K., Katz, A., Sarkar, J., Burland, E., & Goh, C. Y. (2014) · Early Child Development and Care · doi:10.1080/03004430.2014.913586 · Cited by 37
“Our study designs – propensity score matching and stepped-wedge – allow for stronger causal inferences than multivariate regression modeling (Brown & Lilford, 2006; Rubin, 2001), which has been used in many of the evaluations of FDK to date.”
InfluentialAddressing confounding when estimating the effects of latent classes on a distal outcome
Schuler, M. S., Leoutsakos, J., & Stuart, E. A. (2014) · Health Services and Outcomes Research Methodology · doi:10.1007/s10742-014-0122-0 · Cited by 33
“Propensity score methods are standard methods for addressing selection bias in an observational study (Rosenbaum and Rubin 1983; Rubin 2001; Stuart 2010).”
InfluentialLee, T. W., Cho, E., Yim, E. S., Lee, H. S., Ko, Y. K., Kim, B. N., & Kim, S. (2014) · Journal of the American Medical Directors Association · doi:10.1016/j.jamda.2014.07.013 · Cited by 33
Lam, P. H., Gupta, N., Dooley, D. J., Singh, S., Deedwania, P., Zile, M. R., Bhatt, D. L., Morgan, C. J., Pitt, B., Fonarow, G. C., et al. (2018) · The American Journal of Medicine · doi:10.1016/j.amjmed.2018.07.008 · Cited by 36
Does participation in agri-environmental schemes increase eco-efficiency?
Baráth, L., Bakucs, Z., Benedek, Z., Fertő, I., Nagy, Z., Vigh, E. Z., Debrenti, E., & Fogarasi, J. (2023) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2023.167518 · Cited by 32
Government subsidies and income smoothing
Pappas, K., Walker, M., Xu, A. L., & Zeng, C. C. (2024) · Contemporary Accounting Research · doi:10.1111/1911-3846.12947 · Cited by 35
Propensity Score Analysis in R
Keller, B., & Tipton, E. (2016) · Journal of Educational and Behavioral Statistics · doi:10.3102/1076998616631744 · Cited by 32
“…useful in situations in which it is unethical or impossible to randomly assign an intervention (e.g., student retention, Hong & Raudenbush, 2006; special education services, Morgan, Frisco, Farkas, & Hibel, 2010; smoking, Rubin, 2001; mode of child delivery, Li, Kleinman, & Gillman, 2014).”
BackgroundBangalore, S., Guo, Y., Xu, J., Blecker, S., Gupta, N., Feit, F., & Hochman, J. S. (2016) · JAMA Cardiology · doi:10.1001/jamacardio.2016.0785 · Cited by 32
Daniels, T. R., Anderson, J. G., Swords, M. P., Maislin, G., Donahue, R. M. J., Pinsker, E. B., & Quiton, J. D. (2019) · Foot & Ankle International · doi:10.1177/1071100719851468 · Cited by 32
“Subclassification using PS quintiles 33 was used to address potential selection bias when combining patients treated with rhPDGF-BB/B-TCP-collagen with similar control patients treated with autograft, utilizing data from the current RCT and 2 previously published studies.”
Impact assessment of salmon farming on income distribution in remote coastal areas: The Chilean case
Cárdenas‐Retamal, R., Dresdner, J., & Ceballos‐Concha, A. (2021) · Food Policy · doi:10.1016/j.foodpol.2021.102078 · Cited by 35
Is sustainability rating material to the market?
Economidou, C., Gounopoulos, D., Konstantios, D., & Tsiritakis, E. D. (2021) · Financial Management · doi:10.1111/fima.12406 · Cited by 37
“…we introduce State Political Orientation as firms with headquarters in states that vote for the Democratic Party are typically more engaged in ESG activities (Rubin, 2001).14 There is no theoretical ground to expect a relation between this variable and the stock price reaction to firms’ IPOs.”
BackgroundImpact of frontloading of skilled nursing visits on the incidence of 30-day hospital readmission
O’Connor, M. L., Hanlon, A. L., & Bowles, K. H. (2014) · Geriatric Nursing · doi:10.1016/j.gerinurse.2014.02.018 · Cited by 32
The Impact of a Tiered Network on Hospital Choice
Frank, M. B., Hsu, J., Landrum, M. B., & Chernew, M. E. (2015) · Health Services Research · doi:10.1111/1475-6773.12291 · Cited by 32
“To derive propensity scores, we specified logistic regression models at the admission level for the probability of being in the TN group during each tier schedule period (Rubin 2001).”
MethodZhang, Y., Kilgore, M. L., Arora, T., Mujib, M. U., Ekundayo, O. J., Aban, I., Feller, M. A., Desai, R. V., Love, T. E., Allman, R. M., et al. (2011) · International Journal of Cardiology · doi:10.1016/j.ijcard.2011.10.089 · Cited by 32
“Importantly, this model does not include outcomes data and as in RCTs, investigators are blinded to outcomes during study design [9].”
MethodBias Reduction in Quasi-Experiments With Little Selection Theory but Many Covariates
Steiner, P. M., Cook, T. D., Li, W., & Clark, M. H. (2014) · Journal of Research on Educational Effectiveness · doi:10.1080/19345747.2014.978058 · Cited by 31
“We used the PS-logit instead of the PS in the regression model since it is usually more linearly related to the outcome of interest (Rubin, 2001).”
MethodThe Use of Sexually Explicit Material and Its Relationship to Adolescent Sexual Activity
Matković, T., Cohen, N. L., & Štulhofer, A. (2018) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2017.11.305 · Cited by 32
Sommer, A., Lee, M., & Bind, M. (2018) · Humanities and Social Sciences Communications · doi:10.1057/s41599-018-0188-3 · Cited by 37
“Cochran and Rubin (1973); Heckman et al. (1998); and Rubin (2001) have shown that 2 PALGRAVE COMMUNICATIONS | (2018)4:138 |DOI: 10.1057/s41599-018-0188-3 | www.nature.com/palcomms regression can estimate biased causal effects when the true relationship between the background covariates or the…”
BackgroundInfluentialCash transfers and micro-enterprise performance: Theory and quasi-experimental evidence from Kenya
Delius, A. J. S., & Sterck, O. C. (2023) · Journal of Development Economics · doi:10.1016/j.jdeveco.2023.103232 · Cited by 48
Linden, A., & Yarnold, P. R. (2016) · Journal of Evaluation in Clinical Practice · doi:10.1111/jep.12610 · Cited by 31
“As shown in Table 1, many of the standardized differences are substantially greater than zero and nine of the 69 standardized differences are greater than the 0.25 cutoff recommended by Rubin [43].”
InfluentialChang, M., Ahn, J., Kim, N., Lee, P. H., Roh, J., Yoon, S., Kang, S., Lee, S., Kim, Y., Lee, C. W., et al. (2016) · American Heart Journal · doi:10.1016/j.ahj.2016.06.020 · Cited by 31
“The propensity score is a conditional probability of having a particular exposure (CR versus IR) given a set of baseline measured clinical covariates.(16) The propensity score was estimated without regarding outcomes, using a nonparsimonious multivariable logistic-regression model,(17)”
MethodYue, L. Q., Campbell, G., Lu, N. T., Xu, Y., & Zuckerman, B. D. (2016) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543406.2016.1226336 · Cited by 30
“Two-stage design When outcome data are in sight, as illustrated by the example in Section 5.1, “it is essentially impossible to be objective when a variety of analyses are being done, each producing an answer, favorable, neutral, or unfavorable to the investigator’s interests” (Rubin, 2001, p. 170).”
MethodInfluentialChanging the Climate for Banking: The Economic Effects of Credit in a Climate-Vulnerable Area
Mata, D. D., & Resende, G. (2018) · Journal of Development Economics · doi:10.1016/j.jdeveco.2020.102459 · Cited by 31
“Rubin (2001) proposes a set of criteria to check for overlap.”
BackgroundEnergy performance certification and time on the market
Aydın, E., Bohórquez, S., & Brounen, D. (2019) · Journal of Environmental Economics and Management · doi:10.1016/j.jeem.2019.102270 · Cited by 31
Mujib, M. U., Rahman, A.-A. Z., Desai, R. V., Ahmed, M. I., Feller, M. A., Aban, I., Love, T. E., White, M., DEEDWANIA, P. C., Aronow, W. S., et al. (2010) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2010.10.012 · Cited by 31
Ahmed, A., Love, T. E., Sui, X., & Rich, M. W. (2006) · Journal of Cardiac Failure · doi:10.1016/j.cardfail.2006.05.008 · Cited by 31
Crowe, B. J., Lipkovich, I. A., & Wang, O. (2009) · Pharmaceutical Statistics · doi:10.1002/pst.389 · Cited by 31
Venture capital as a catalyst for commercialization and high growth
Kelly, R., & Kim, H. (2016) · The Journal of Technology Transfer · doi:10.1007/s10961-016-9540-1 · Cited by 33
The relationship between intergenerational transfers, housing and economic outcomes
Barrett, G. F., Cigdem, M., Whelan, S., & Wood, G. (2015) · eSpace (Curtin University) · Cited by 30
Does e-shopping impact household travel? Evidence from the 2017 U.S. NHTS
Xu, L., & Saphores, J.-D. M. (2024) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2024.103827 · Cited by 30
Kheirbek, R., Fletcher, R. D., Bakitas, M. A., Fonarow, G. C., Parvataneni, S., Bearden, D. M., Bailey, F. A., Morgan, C. J., Singh, S. N., Blackman, M. R., et al. (2015) · Circulation Heart Failure · doi:10.1161/circheartfailure.115.002153 · Cited by 30
Discontinuation and comparative effectiveness of dimethyl fumarate and fingolimod in 2 centers
Vollmer, B. L., Ontaneda, D., Bandyopadhyay, A., Cohn, S., Nair, K. V., Sillau, S., Bermel, R. A., Corboy, J. R., Fox, R. J., Vollmer, T. R., et al. (2018) · Neurology Clinical Practice · doi:10.1212/cpj.0000000000000487 · Cited by 30
“3%, well within the 50% standard proposed by Rubin.(17)”
InfluentialRituximab versus natalizumab, fingolimod, and dimethyl fumarate in multiple sclerosis treatment
Vollmer, B. L., Nair, K. V., Sillau, S., Corboy, J. R., Vollmer, T. R., & Álvarez, E. (2020) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.51111 · Cited by 31
“1%, well within the 50% standard proposed by Rubin.(18) Effectiveness outcomes”
BackgroundInfluentialSystolic Blood Pressure and Outcomes in Older Patients with HFpEF and Hypertension
Faselis, C. J., Lam, P. H., Zile, M. R., Bhyan, P., Tsimploulis, A., Arundel, C., Patel, S. S., Kokkinos, P. F., DEEDWANIA, P. C., Bhatt, D. L., et al. (2020) · The American Journal of Medicine · doi:10.1016/j.amjmed.2020.08.030 · Cited by 30
Dalal, R. S., Mitri, J., Goodrick, H., & Allegretti, J. R. (2021) · Inflammatory Bowel Diseases · doi:10.1093/ibd/izab097 · Cited by 30
Achim, A., Szigethi, T., Olajos, D. L., Molnár, L., Papp, R., Bárczi, G., Kákonyi, K. M., Edes, I. F., Becker, D. J., Merkely, B. P., et al. (2022) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2022.895457 · Cited by 30
Oral potassium supplement use and outcomes in chronic heart failure: A propensity-matched study
Ekundayo, O. J., Adamopoulos, C., Ahmed, M. I., Pitt, B., Young, J. B., Fleg, J. L., Love, T. E., Sui, X., Perry, G. J., Siscovick, D. S., et al. (2009) · International Journal of Cardiology · doi:10.1016/j.ijcard.2008.11.195 · Cited by 30
A propensity-matched study of outcomes of chronic heart failure (HF) in younger and older adults
Wahle, C., Adamopoulos, C., Ekundayo, O. J., Mujib, M. U., Aronow, W. S., & Ahmed, A. (2008) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2008.06.009 · Cited by 30
“First, we used a non-parsimonious multivariable logistic regression model to calculate, for each patient, a propensity score for having age 65 years (Rosenbaum and Rubin, 1983, 1984; Rubin, 1997, 2001, 2004; Ahmed et al., 2006a, 2006b, 2007a, 2007b; Ahmed and Aronow, 2008).”
First-Generation College Student Achievement and the First-Year Seminar: A Quasi-Experimental Design
Vaughan, A. L., Parra, J. M., & Lalonde, T. L. (2014) · Journal of The First-Year Experience & Students in Transition · doi:10.65005/154230714814006040 · Cited by 30
Bray, B. C., Dziak, J. J., Patrick, M. E., & Lanza, S. T. (2018) · Prevention Science · doi:10.1007/s11121-018-0883-8 · Cited by 30
“A large body of literature has discussed the limitations of approaches where some number of potential confounders are added directly to the outcome analysis in order to control for them (e.g., Dehejia and Wahba 2002; Rubin 2001).”
Movement synchrony and attachment related anxiety and avoidance in social anxiety disorder.
Schoenherr, D., Strauss, B., Paulick, J., Deisenhofer, A.-K., Schwartz, B., Rubel, J. A., Boyle, K., Lutz, W., Stangier, U., & Altmann, U. (2021) · Journal of Psychotherapy Integration · doi:10.1037/int0000187 · Cited by 29
Incentivizing angels to invest in start-ups: Evidence from a natural experiment
Solodoha, E., Rosenzweig, S., & Harel, S. (2022) · Research Policy · doi:10.1016/j.respol.2022.104634 · Cited by 31
Propensity Score Analysis With Fallible Covariates
Raykov, T. (2012) · Educational and Psychological Measurement · doi:10.1177/0013164412440999 · Cited by 30
“Hence, the mean group difference in MPS was only 7% of their weighted average standard deviation (cf. Rubin, 2001).”
BackgroundAdams, N., Tudehope, D., GIBBONS, K. S., & Flenady, V. (2017) · BJOG An International Journal of Obstetrics & Gynaecology · doi:10.1111/1471-0528.14903 · Cited by 29
Bangalore, S., Cohen, D. J., Kleiman, N. S., Regev-Beinart, T., Rao, S. V., Pencina, M. J., & Mauri, L. (2011) · Circulation Cardiovascular Interventions · doi:10.1161/circinterventions.111.961912 · Cited by 29
Wordsworth, S., Doble, B., Payne, K., Buchanan, J. P., Marshall, D. A., McCabe, C. J., & Regier, D. A. (2018) · Value in Health · doi:10.1016/j.jval.2018.06.016 · Cited by 29
The wage premium from foreign language skills
Liwiński, J. (2019) · Empirica · doi:10.1007/s10663-019-09459-0 · Cited by 29
“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.”
BackgroundInfluentialPropensity weighting: how to minimise comparative bias in non-randomised studies?
Moons, P. (2019) · European Journal of Cardiovascular Nursing · doi:10.1177/1474515119888972 · Cited by 29
Singh, S. N., Moore, H. J., Karasik, P., Lam, P. H., Wopperer, S. B., Arundel, C., Tummala, L. S., Anker, M. S., Faselis, C. J., DEEDWANIA, P. C., et al. (2020) · The American Journal of Medicine · doi:10.1016/j.amjmed.2020.05.030 · Cited by 29
Deng, Z., & Law, Y. W. (2020) · PLoS ONE · doi:10.1371/journal.pone.0244441 · Cited by 29
Adoption of conservation agriculture-based tillage practices in the rice-maize systems in Bangladesh
Akter, S., Gathala, M. K., Timsina, J., Islam, S., Rahman, M., Hassan, M. K., & Ghosh, A. K. (2021) · World Development Perspectives · doi:10.1016/j.wdp.2021.100297 · Cited by 31
Agricultural value chain development in Nepal: Understanding mechanisms for poverty reduction
Kafle, K., Songsermsawas, T., & Winters, P. (2022) · Agricultural Economics · doi:10.1111/agec.12696 · Cited by 30
Shen, X., Qiu, Y. L., Liu, P., & Patwardhan, A. (2022) · Environmental and Resource Economics · doi:10.1007/s10640-022-00691-0 · Cited by 29
“According to Rubin (2001), if SMD is smaller than 0.25 and VR is in the range between 0.5 and 2, the treatment and control groups are balanced for this covariate in terms of mean and distribution.”
MethodInfluentialIs parental involvement lower at larger schools?
Walsh, P. (2010) · Economics of Education Review · doi:10.1016/j.econedurev.2010.04.003 · Cited by 29
Late Outcomes After Carotid Artery Stenting Versus Carotid Endarterectomy
Bangalore, S., Bhatt, D. L., Röther, J., Alberts, M. J., Thornton, J., Wolski, K., Goto, S., Hirsch, A. T., Smith, S. C., Aichner, F., et al. (2010) · Circulation · doi:10.1161/circulationaha.109.933341 · Cited by 29
Hogrebe, N., & Strietholt, R. (2016) · Large-scale Assessments in Education · doi:10.1186/s40536-016-0017-3 · Cited by 31
“The ratio of the variances of the propensity scores and the ratio of the variances for the residuals of the covariates after adjusting for the propensity scores should be close to one (e.g. between 0.5 and 2; Rubin 2001).”
BackgroundInfluentialStatistical innovations in the medical device world sparked by the FDA
Campbell, G., & Yue, L. Q. (2015) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543406.2015.1092037 · Cited by 28
“For such a situation, Rubin (2001) states “it is essentially impossible to be objective when a variety of analyses are being done, each producing an answer, favorable, neutral, or unfavorable to the investigator’s interests.””
BackgroundMethodBangalore, S., Bhagwat, A. R., Pinto, B., Goel, P., Jagtap, P., Sathe, S., Arambam, P., & Kaul, U. (2016) · JAMA Cardiology · doi:10.1001/jamacardio.2016.0305 · Cited by 29
What are the trade-offs of academic entrepreneurship? An investigation on the Italian case
Barbieri, E., Rubini, L., Pollio, C., & Micozzi, A. (2016) · The Journal of Technology Transfer · doi:10.1007/s10961-016-9482-7 · Cited by 29
Chasing Balance and Other Recommendations for Improving Nonparametric Propensity Score Models
Griffin, B. A., McCaffrey, D. F., Almirall, D., Burgette, L. F., & Setodji, C. M. (2017) · Journal of Causal Inference · doi:10.1515/jci-2015-0026 · Cited by 31
“, the probability of being assigned to treatment given a set pre-treatment predictors) to balance treatment groups has rapidly gained popularity in many fields where observational studies are the norm [1, 2].”
BackgroundFemale Land Ownership and Fertility in Nepal
Chakrabarti, A. (2017) · The Journal of Development Studies · doi:10.1080/00220388.2017.1400017 · Cited by 26
“In the literature on propensity score matching and weighting, the following standards are taken to be indicative of covariate balance – absolute standardised differences in means of 0.1 or less, and ratios of variances close to one (Austin, 2011; Normand et al., 2001; Rubin, 2001).”
BackgroundInfluentialMatching and Weighting With Functions of Error-Prone Covariates for Causal Inference
Lockwood, J. R., & McCaffrey, D. F. (2015) · Journal of the American Statistical Association · doi:10.1080/01621459.2015.1122601 · Cited by 35
Factors associated with private-public school performance: Analysis of TALIS-PISA link data
Delprato, M., & Chudgar, A. (2018) · International Journal of Educational Development · doi:10.1016/j.ijedudev.2018.01.002 · Cited by 28
Yoon, T. J. (2019) · Marketing Science · doi:10.1287/mksc.2018.1146 · Cited by 28
Association of Contrast and Acute Kidney Injury in the Critically Ill
Williams, L.-M. S., Walker, G. R., Loewenherz, J. W., & Gidel, L. T. (2019) · CHEST Journal · doi:10.1016/j.chest.2019.10.005 · Cited by 28
Does Starting Universal Childcare Earlier Influence Children’s Skill Development?
Kuehnle, D., & Oberfichtner, M. (2020) · Demography · doi:10.1007/s13524-019-00836-9 · Cited by 28
Inventory investment and the choice of financing: Does financial development play a role?
Yang, J., Guariglia, A., Peng, Y., & Shi, Y. (2022) · Journal of Corporate Finance · doi:10.1016/j.jcorpfin.2021.102139 · Cited by 28
Real world comparison of spironolactone and eplerenone in patients with heart failure
Pardo-Martínez, P., Barge‐Caballero, E., Bouzas‐Mosquera, A., Barge‐Caballero, G., Couto‐Mallón, D., Paniagua-Martín, M. J., Sagastagoitia-Fornie, M., Prada‐Delgado, Ó., Muñiz, J., Bonet, L. A., et al. (2022) · European Journal of Internal Medicine · doi:10.1016/j.ejim.2021.12.027 · Cited by 28
Regulatory Considerations in the Design of Comparative Observational Studies Using Propensity Scores
Yue, L. Q. (2012) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543406.2012.715111 · Cited by 28
Comparative Effectiveness of Oral Versus Outpatient Parenteral Antibiotic Therapy for Empyema
Stockmann, C. R., Ampofo, K., Pavia, A. T., Byington, C. L., Sheng, X., Greene, T., Korgenski, E. K., & Hersh, A. L. (2015) · Hospital Pediatrics · doi:10.1542/hpeds.2015-0100 · Cited by 28
Mishra, G. S., Mokhtarian, P. L., Clewlow, R., & Widaman, K. F. (2017) · Transportation · doi:10.1007/s11116-017-9791-1 · Cited by 28
New evidence on long-term effects of start-up subsidies: matching estimates and their robustness
Caliendo, M., & Tübbicke, S. (2019) · Empirical Economics · doi:10.1007/s00181-019-01701-9 · Cited by 28
“The balancing measures based on the propensity score due to Rubin (2001) also point toward a drastic increase in balancing quality.”
Blomberg, A. J., Nyhan, M., Bind, M., Vokonas, P., Coull, B. A., Schwartz, J. D., & Koutrakis, P. (2020) · Epidemiology · doi:10.1097/ede.0000000000001197 · Cited by 29
Shao, R., Derudder, B., & Yang, Y. (2022) · Sustainable Cities and Society · doi:10.1016/j.scs.2022.104204 · Cited by 27
Cheating when in the hole: The case of New York city taxis
Rajgopal, S., & White, R. (2019) · Accounting, Organizations and Society · doi:10.1016/j.aos.2019.101070 · Cited by 25
Crisafulli, E., Guerrero, M., Ielpo, A., Ceccato, A., Huerta, A. H., Gabarrús, A., Soler, N., Chetta, A. A., & Torres, A. (2018) · Scientific Reports · doi:10.1038/s41598-018-27680-y · Cited by 27
Are shareholders gender neutral? Evidence from say on pay
Canil, J., Karpavičius, S., & Yu, C. (2019) · Journal of Corporate Finance · doi:10.1016/j.jcorpfin.2019.05.004 · Cited by 25
“Panel A reports the distribution of the control variables after EB, and shows that none of the standardized differences and variance ratios is outside of the vertical bands following the guidance in Rubin (2001) and Austin (2011).”
BackgroundHeiden, B. T., Eaton, D. B., Chang, S., Yan, Y., Schoen, M. W., Patel, M. R., Kreisel, D., Nava, R. G., Meyers, B. F., Kozower, B. D., et al. (2021) · Annals of Surgery · doi:10.1097/sla.0000000000004928 · Cited by 27
Owusu, E. S., & Bravo‐Ureta, B. E. (2021) · The Journal of Development Studies · doi:10.1080/00220388.2021.2008364 · Cited by 27
“We chose the radius-matching algorithm given that better quality matches were obtained on the basis of the percentage reduction in absolute bias, and Rubin’s B and R compared to other algorithms common to the empirical literature (Austin, 2011; Rubin, 2001).”
MethodLindner, C., Kotta, I., Marschalkó, E. E., Szabó, K., Kálcza-Jánosi, K., & Retelsdorf, J. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19095098 · Cited by 30
The Role of Privacy Fatigue in Privacy Paradox: A PSM and Heterogeneity Analysis
Tian, X., Chen, L., & Zhang, X. (2022) · Applied Sciences · doi:10.3390/app12199702 · Cited by 27
Creating visibility: voluntary disclosure by private firms pursuing an initial public offering
Dambra, M., Schonberger, B., & Wasley, C. E. (2018) · Review of Accounting Studies · doi:10.1007/s11142-023-09763-y · Cited by 27
“Entropy balancing eliminates this imbalance such that standardized differences are near zero and the bulk of variance ratios are near one, consistent with balanced covariates (Rubin 2001).”
Ex-ante litigation risk and firm-level climate-change exposure
Hossain, A. T., Rjiba, H., & Zhang, D. (2023) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2023.09.008 · Cited by 27
Ritchie, C. S., Ekundayo, O. J., Muchimba, M., Campbell, R. C., Frank, S. J., Liu, B., Aban, I., & Ahmed, A. (2009) · International Journal of Cardiology · doi:10.1016/j.ijcard.2008.12.089 · Cited by 27
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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