References

Alam, Shomoita, Erica EM Moodie, and David A Stephens. 2019. “Should a Propensity Score Model Be Super? The Utility of Ensemble Procedures for Causal Adjustment.” Statistics in Medicine 38 (9): 1690–1702.
Ali, M Sanni, Daniel Prieto-Alhambra, Luciane Cruz Lopes, Dandara Ramos, Nivea Bispo, Maria Y Ichihara, Julia M Pescarini, et al. 2019. “Propensity Score Methods in Health Technology Assessment: Principles, Extended Applications, and Recent Advances.” Frontiers in Pharmacology 10: 973.
Athey, Susan, and Stefan Wager. 2019. “Estimating Treatment Effects with Causal Forests: An Application.” Observational Studies 5 (2): 37–51.
Austin, Peter C. 2007. “Propensity-Score Matching in the Cardiovascular Surgery Literature from 2004 to 2006: A Systematic Review and Suggestions for Improvement.” The Journal of Thoracic and Cardiovascular Surgery 134 (5): 1128–35.
———. 2009. “Balance Diagnostics for Comparing the Distribution of Baseline Covariates Between Treatment Groups in Propensity-Score Matched Samples.” Statistics in Medicine 28 (25): 3083–3107.
———. 2011a. “A Tutorial and Case Study in Propensity Score Analysis: An Application to Estimating the Effect of in-Hospital Smoking Cessation Counseling on Mortality.” Multivariate Behavioral Research 46 (1): 119–51.
———. 2011b. “An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies.” Multivariate Behavioral Research 46 (3): 399–424.
Austin, Peter C, and Dylan S Small. 2014. “The Use of Bootstrapping When Using Propensity-Score Matching Without Replacement: A Simulation Study.” Statistics in Medicine 33 (24): 4306–19.
Balzer, Laura B, and Ted Westling. 2021. “Demystifying Statistical Inference When Using Machine Learning in Causal Research.” American Journal of Epidemiology.
Breiman, L, JH Friedman, R Olshen, and CJ Stone. 1984. “Classification and Regression Trees.”
Brookhart, M Alan, Sebastian Schneeweiss, Kenneth J Rothman, Robert J Glynn, Jerry Avorn, and Til Stürmer. 2006. “Variable Selection for Propensity Score Models.” American Journal of Epidemiology 163 (12): 1149–56.
Chernozhukov, Victor, Denis Chetverikov, Mert Demirer, Esther Duflo, Christian Hansen, and Whitney Newey. 2017. “Double/Debiased/Neyman Machine Learning of Treatment Effects.” American Economic Review 107 (5): 261–65.
D’Agostino Jr, Ralph B. 1998. “Propensity Score Methods for Bias Reduction in the Comparison of a Treatment to a Non-Randomized Control Group.” Statistics in Medicine 17 (19): 2265–81.
Dong, Jing, Junni L Zhang, Shuxi Zeng, and Fan Li. 2020. “Subgroup Balancing Propensity Score.” Statistical Methods in Medical Research 29 (3): 659–76.
Eeren, Hester V, Marieke D Spreeuwenberg, Anna Bartak, Mark de Rooij, and Jan JV Busschbach. 2015. “Estimating Subgroup Effects Using the Propensity Score Method: A Practical Application in Outcomes Research.” Medical Care 53 (4): 366–73.
Gautret, Philippe, Jean-Christophe Lagier, Philippe Parola, Line Meddeb, Morgane Mailhe, Barbara Doudier, Johan Courjon, et al. 2020. “Hydroxychloroquine and Azithromycin as a Treatment of COVID-19: Results of an Open-Label Non-Randomized Clinical Trial.” International Journal of Antimicrobial Agents 56 (1): 105949.
Girman, Cynthia J, Mugdha Gokhale, Tzuyung Doug Kou, Kimberly G Brodovicz, Richard Wyss, and Til Stürmer. 2014. “Assessing the Impact of Propensity Score Estimation and Implementation on Covariate Balance and Confounding Control Within and Across Important Subgroups in Comparative Effectiveness Research.” Medical Care 52 (3): 280.
Green, Kerry M, and Elizabeth A Stuart. 2014. “Examining Moderation Analyses in Propensity Score Methods: Application to Depression and Substance Use.” Journal of Consulting and Clinical Psychology 82 (5): 773.
Ho, Tin Kam. 1995. “Random Decision Forests.” In Proceedings of 3rd International Conference on Document Analysis and Recognition, 1:278–82. IEEE.
Kang, Joseph DY, and Joseph L Schafer. 2007. “Demystifying Double Robustness: A Comparison of Alternative Strategies for Estimating a Population Mean from Incomplete Data.” Statistical Science 22 (4): 523–39.
Karim, Mohammad Ehsanul, Menglan Pang, and Robert W Platt. 2018. “Can We Train Machine Learning Methods to Outperform the High-Dimensional Propensity Score Algorithm?” Epidemiology 29 (2): 191–98.
Karim, Mohammad Ehsanul, Fabio Pellegrini, Robert W Platt, Gabrielle Simoneau, Julie Rouette, and Carl de Moor. 2020. “The Use and Quality of Reporting of Propensity Score Methods in Multiple Sclerosis Literature: A Review.” Multiple Sclerosis Journal, 1352458520972557.
King, Gary, and Richard Alexander Nielsen. 2019. “Why Propensity Scores Should Not Be Used for Matching.”
Kreif, Noemi, Richard Grieve, Rosalba Radice, Zia Sadique, Roland Ramsahai, and Jasjeet S Sekhon. 2012. “Methods for Estimating Subgroup Effects in Cost-Effectiveness Analyses That Use Observational Data.” Medical Decision Making 32 (6): 750–63.
Lee, Brian K, Justin Lessler, and Elizabeth A Stuart. 2010. “Improving Propensity Score Weighting Using Machine Learning.” Statistics in Medicine 29 (3): 337–46.
Liu, Shan-Yu, Chunyan Liu, Eddie Nehus, Maurizio Macaluso, Bo Lu, and Mi-Ok Kim. 2020. “Propensity Score Analysis for Correlated Subgroup Effects.” Statistical Methods in Medical Research 29 (4): 1067–80.
Naimi, Ashley I, Alan E Mishler, and Edward H Kennedy. 2017. “Challenges in Obtaining Valid Causal Effect Estimates with Machine Learning Algorithms.” arXiv Preprint arXiv:1711.07137.
Nguyen, Tri-Long, Gary S Collins, Jessica Spence, Jean-Pierre Daurès, PJ Devereaux, Paul Landais, and Yannick Le Manach. 2017. “Double-Adjustment in Propensity Score Matching Analysis: Choosing a Threshold for Considering Residual Imbalance.” BMC Medical Research Methodology 17 (1): 1–8.
Pirracchio, Romain, Maya L Petersen, and Mark Van Der Laan. 2015. “Improving Propensity Score Estimators’ Robustness to Model Misspecification Using Super Learner.” American Journal of Epidemiology 181 (2): 108–19.
Radice, Rosalba, Roland Ramsahai, Richard Grieve, Noemi Kreif, Zia Sadique, and Jasjeet S Sekhon. 2012. “Evaluating Treatment Effectiveness in Patient Subgroups: A Comparison of Propensity Score Methods with an Automated Matching Approach.” The International Journal of Biostatistics 8 (1).
Rassen, Jeremy A, Robert J Glynn, Kenneth J Rothman, Soko Setoguchi, and Sebastian Schneeweiss. 2012. “Applying Propensity Scores Estimated in a Full Cohort to Adjust for Confounding in Subgroup Analyses.” Pharmacoepidemiology and Drug Safety 21 (7): 697–709.
Robins, J. M., and A G Rotnitzky. 2001. “Comment on the Bickel and Kwon Article, ’Inference for Semiparametric Models: Some Questions and an Answer’.” Statistica Sinica 11 (January): 920–36.
Robins, James. 1986. “A New Approach to Causal Inference in Mortality Studies with a Sustained Exposure Period—Application to Control of the Healthy Worker Survivor Effect.” Mathematical Modelling 7 (9-12): 1393–1512.
Rosenbaum, Paul R, and Donald B Rubin. 1983. “The Central Role of the Propensity Score in Observational Studies for Causal Effects.” Biometrika 70 (1): 41–55.
Rubin, Donald B. 1973. “Matching to Remove Bias in Observational Studies.” Biometrics, 159–83.
Stanton, Jeffrey M. 2001. “Galton, Pearson, and the Peas: A Brief History of Linear Regression for Statistics Instructors.” Journal of Statistics Education 9 (3).
Stuart, Elizabeth A. 2010. “Matching Methods for Causal Inference: A Review and a Look Forward.” Statistical Science: A Review Journal of the Institute of Mathematical Statistics 25 (1): 1.
Van Der Laan, Mark J, and Daniel Rubin. 2006. “Targeted Maximum Likelihood Learning.” The International Journal of Biostatistics 2 (1).
Wang, Shirley V, Yinzhu Jin, Bruce Fireman, Susan Gruber, Mengdong He, Richard Wyss, HoJin Shin, et al. 2018. “Relative Performance of Propensity Score Matching Strategies for Subgroup Analyses.” American Journal of Epidemiology 187 (8): 1799–1807.
Yang, Dongsheng, and Jarrod E Dalton. 2012. “A Unified Approach to Measuring the Effect Size Between Two Groups Using SAS.” In SAS Global Forum, 335:1–6. Citeseer.
Yao, Xiaoxin I, Xiaofei Wang, Paul J Speicher, E Shelley Hwang, Perry Cheng, David H Harpole, Mark F Berry, Deborah Schrag, and Herbert H Pang. 2017. “Reporting and Guidelines in Propensity Score Analysis: A Systematic Review of Cancer and Cancer Surgical Studies.” JNCI: Journal of the National Cancer Institute 109 (8): djw323.