Results 11 to 20 of about 4,704,446 (291)
Mhbounds - Sensitivity Analysis for Average Treatment Effects [PDF]
SSRN Electronic Journal, 2007 Matching has become a popular approach to estimate average treatment effects. It is based on the conditional independence or unconfoundedness assumption. Checking the sensitivity of the estimated results with respect to deviations from this identifying assumption has become an increasingly important topic in the applied evaluation literature.
Sascha O. Becker, Marco Caliendo
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Latent class instrumental variables and the monotonicity assumption
Emerging Themes in Epidemiology, 2020 A key aspect of the article by Lousdal on instrumental variables was a discussion of the monotonicity assumption. However, there was no mention of the history of the development of this assumption.
Stuart G. Baker
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Uluslararası Türk Eğitim Bilimleri Dergisi, 2023 In this Monte Carlo simulation study, the performance of six different propensity score methods implemented through weighting cases was investigated: inverse probability of treatment weighting, truncated inverse probability of treatment weighting ...
Sungur Gürel, Walter Lana Leite
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An Exponential Endogenous Switching Regression with Correlated Random Coefficients
Econometrics, 2021 This paper presents a method for estimating the average treatment effects (ATE) of an exponential endogenous switching model where the coefficients of covariates in the structural equation are random and correlated with the binary treatment variable. The
Myoung-Jin Keay
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Cogent Business & Management, 2022 Purpose This study assessed the effect of E-commerce on sales performance of agrochemical input dealers in the Greater Accra Region of Ghana.Design/methodology/approach The study utilized both primary and secondary data.
Benjamin Nyarko +3 more
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Individualized treatment rules under stochastic treatment cost constraints
Journal of Causal Inference, 2022 Estimation and evaluation of individualized treatment rules have been studied extensively, but real-world treatment resource constraints have received limited attention in existing methods.
Qiu Hongxiang +2 more
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Evaluation of Educational Interventions Based on Average Treatment Effect: A Case Study
Mathematics, 2022 Relative to randomized controlled trials (RCTs) with privacy and ethical concerns, observational studies are becoming dominant in education research. In an observational study, it is necessary and important to correctly evaluate the effects of different ...
Jingyu Liang, Jie Liu
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Estimating Conditional Average Treatment Effects [PDF]
Journal of Business & Economic Statistics, 2014 We consider a functional parameter called the conditional average treatment effect (CATE), designed to capture the heterogeneity of a treatment effect across subpopulations when the unconfoundedness assumption applies. In contrast to quantile regressions, the subpopulations of interest are defined in terms of the possible values of a set of continuous ...
Jason Abrevaya +2 more
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Information Bottleneck for Estimating Treatment Effects with Systematically Missing Covariates
Entropy, 2020 Estimating the effects of an intervention from high-dimensional observational data is a challenging problem due to the existence of confounding. The task is often further complicated in healthcare applications where a set of observations may be entirely ...
Sonali Parbhoo +3 more
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Sensitivity Analysis for Average Treatment Effects [PDF]
The Stata Journal: Promoting communications on statistics and Stata, 2007 Based on the conditional independence or unconfoundedness assumption, matching has become a popular approach to estimate average treatment effects. Checking the sensitivity of the estimated results with respect to deviations from this identifying assumption has become an increasingly important topic in the applied evaluation literature.
Sascha O. Becker, Marco Caliendo
openaire +2 more sources