Results 31 to 40 of about 4,735,813 (292)
Estimation of Average Treatment Effects with Misclassification [PDF]
This paper considers identification and estimation of the effect of a mismeasured binary regressor in a nonparametric or semiparametric regression, or the conditional average effect of a binary treatment or policy on some outcome where treatment may be misclassified.
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The purpose of the paper was to introduce how to reasonably carry out multiple Logistic regression analysis combined with the average treatment effect analysis.
Hu Chunyan, Hu Liangping
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Testing Local Average Treatment Effect Assumptions [PDF]
In this paper, we propose an easy-to-implement procedure to test the key conditions for the identification and estimation of the local average treatment effect (LATE; Imbens & Angrist, 1994). We reformulate the testable implications of LATE assumptions as two conditional inequalities, which can be tested in the intersection bounds framework of ...
Ismael Mourifie, Yuanyuan Wan
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Semiparametric Single-Index Estimation for Average Treatment Effects
We propose a semiparametric method to estimate the average treatment effect under the assumption of unconfoundedness given observational data. Our estimation method alleviates misspecification issues of the propensity score function by estimating the single-index link function involved through Hermite polynomials.
Difang Huang, Jiti Gao, Tatsushi Oka
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Introduction: Appropriate complementary foods have been found to provide infants and young children with nutritional needs for their growth and development.
Halima S. Twabi +3 more
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Inference on Local Average Treatment Effects for Misclassified Treatment [PDF]
43 pages, 1 figure, 7 tables, 1 ...
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School entry, educational attainment, and quarter of birth: a cautionary tale of a local average treatment effect [PDF]
Studies of the effects of school entry age on short-run and long-run outcomes generally fail to capture the parameter of policy interest and/or are inconsistent because the instrument they use violates monotonicity, required for identification of a local
Barua, Rashmi, Lang, Kevin
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Propensity Score Matching: should we use it in designing observational studies?
Background Propensity Score Matching (PSM) stands as a widely embraced method in comparative effectiveness research. PSM crafts matched datasets, mimicking some attributes of randomized designs, from observational data.
Fei Wan
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Bounding average treatment effects: A linear programming approach [PDF]
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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ABSTRACT Purpose Retinoblastoma (RB) is the most common pediatric ocular cancer, yet population‐based data on survival and risk factors remain limited. This study aimed to describe survival in a large national RB cohort and identify predictors of death and complications.
Samuel Sassine +14 more
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