Results 71 to 80 of about 4,712,566 (254)
Linear Estimation of Global Average Treatment Effects
We study the problem of estimating the average causal effect of treating every member of a population, as opposed to none, using an experiment that treats only some. We consider settings where spillovers have global support and decay slowly with (a generalized notion of) distance.
Faridani, Stefan, Niehaus, Paul
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Treatment Decision‐Making Roles and Preferences Among Adolescents and Young Adults With Cancer
ABSTRACT Background Decision‐making (DM) dynamics between adolescents and young adults (AYAs) with cancer, parents, and oncologists remain underexplored in diverse populations. We examined cancer treatment DM preferences among an ethnically and socioeconomically diverse group of AYAs and their parents.
Amanda M. Gutierrez +14 more
wiley +1 more source
Estimating Average Treatment Effects With Support Vector Machines
ABSTRACTSupport vector machine (SVM) is one of the most popular classification algorithms in the machine learning literature. We demonstrate that SVM can be used to balance covariates and estimate average causal effects under the unconfoundedness assumption.
Alexander Tarr, Kosuke Imai
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Estimation of Average Treatment Effects Based on Propensity Scores [PDF]
In this paper, we give a short overview of some propensity score matching estimators suggested in the evaluation literature, and we provide a set of Stata programs, which we illustrate using the National Supported Work (NSW) demonstration widely known in labor economics.
Sascha O. Becker, Andrea Ichino
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ABSTRACT Background Parents of children treated for acute lymphoblastic leukemia (ALL) often experience significant caregiver burden and disruption to their well‐being. While parent quality of life (QoL) during treatment is well characterized, little is known about outcomes during early survivorship.
Sara Dal Pra +3 more
wiley +1 more source
A Meta-Learning Approach for Estimating Heterogeneous Treatment Effects Under Hölder Continuity
Estimating heterogeneous treatment effects plays a vital role in many statistical applications, such as precision medicine and precision marketing. In this paper, we propose a novel meta-learner, termed RXlearner for estimating the conditional average ...
Zhihao Zhao, Congyang Zhou
doaj +1 more source
Based on different motivations for engaging in outward FDI, this study divides firms' outward FDI into five types: non-FDI, FDI, defensive only outward FDI, expansive only outward FDI, and both defensive & expansive outward FDI simultaneously, and ...
Hui-Lin Lin, Yi-Chi Hsiao, Eric S. Lin
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Efficient Estimation of Average Treatment Effect on the Treated under Endogenous Treatment Assignment [PDF]
Trinetri Ghosh, Menggang Yu, Jiwei Zhao
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ABSTRACT A second allogeneic (allo‐)hematopoietic stem cell transplantation (HSCT2) is a potential curative option for pediatric patients with acute lymphoblastic leukemia (ALL) following relapse after first allogeneic transplantation (HSCT1), but its efficacy is limited by high relapse rates and transplant‐related toxicity in highly pretreated ...
Ava Momm +10 more
wiley +1 more source
Efficient Estimation of Average Treatment Effects Under Treatment-Based Sampling [PDF]
Nonrandom sampling schemes are often used in program evaluation settings to improve the quality of inference. This paper considers what we call treatment-based sampling, a type of standard stratified sampling where part of the strata are based on treatments.
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