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Matching using semiparametric propensity scores [PDF]
Empirical Economics, 2012 This paper considers the application of semiparametric methods to estimate propensity scores or probabilities of program participation, which are central to certain program evaluation methods. To evaluate the practical benefits, we first conduct a Monte Carlo study. Second, we use data from the NSW experiment, CPS, and PSID. We compare treatment effect
Steven Lehrer, Gregory Kordas
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ISOTONIC PROPENSITY SCORE MATCHING
Econometric TheoryWe propose a one-to-many matching estimator of the average treatment effect based on propensity scores estimated by isotonic regression. This approach is predicated on the assumption of monotonicity in the propensity score function, a condition that can be justified in many economic applications.
Xu, Mengshan, Otsu, Taisuke
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Propensity score matching and complex surveys [PDF]
Statistical Methods in Medical Research, 2016 Researchers are increasingly using complex population-based sample surveys to estimate the effects of treatments, exposures and interventions. In such analyses, statistical methods are essential to minimize the effect of confounding due to measured covariates, as treated subjects frequently differ from control subjects.
Austin, Peter C +2 more
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Annals of Gastroenterological Surgery, 2022 Aim This study aimed to clarify the clinical effects of the indocyanine green (ICG)‐fluorescence imaging (FI) technique for determination of liver transection lines during laparoscopic partial liver resection for liver tumors.
Shinji Itoh +9 more
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Matching on Generalized Propensity Scores with Continuous Exposures
Journal of the American Statistical Association, 2022 In the context of a binary treatment, matching is a well-established approach in causal inference. However, in the context of a continuous treatment or exposure, matching is still underdeveloped. We propose an innovative matching approach to estimate an average causal exposure-response function under the setting of continuous exposures that relies on ...
Xiao Wu +4 more
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Generalized Propensity Score Matching with Multilevel Treatment Options
Journal of Health Economics and Outcomes Research, 2013 # Background Although conventional form of propensity score matching (PSM) is widely used in outcomes research field, its application on multilevel treatment is limited. # Objectives This article reviews PSM and illustrates their use when there are more
Onur Baser
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European Journal of Radiology Open, 2018 Purpose: To assess the filter tilting and outcomes of the Celect and Denali inferior vena cava (IVC) filters by using a propensity score-matching analysis.
Jae Heung Bae, Sang Yub Lee
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Journal of Comparative Effectiveness Research, 2018 Aim: A comparison of conventional pairwise propensity score matching (PSM) and generalized PSM method was applied to the comparative effectiveness of multiple treatment options for lung cancer. Materials & methods: Deidentified data were analyzed.
Zhanglin L, Cui +3 more
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Propensity Score Matching in Randomized Clinical Trials [PDF]
Biometrics, 2009 Summary Cluster randomization trials with relatively few clusters have been widely used in recent years for evaluation of health‐care strategies. On average, randomized treatment assignment achieves balance in both known and unknown confounding factors between treatment groups, however, in practice investigators can only introduce a small amount of ...
Xu, Zhenzhen, Kalbfleisch, John D.
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Jambura Journal of MathematicsResearch on complications of Diabetes Mellitus (DM) is multifactorial, where the risk factors causing DM complications are interrelated, leading to confounding bias, which results in inaccurate research findings. Confounding bias can be reduced using the
Ingka Rizkyani Akolo +2 more
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