Exploring Marginal Treatment Effects: Flexible Estimation Using Stata
The Stata Journal: Promoting communications on statistics and Stata, 2018 In settings that exhibit selection on both levels and gains, marginal treatment effects (MTE) allow us to go beyond local average treatment effects and estimate the whole distribution of effects.
M. Andresen
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Estimating Marginal Treatment Effects in Heterogeneous Populations [PDF]
Annales d'Économie et de Statistique, 2008 R. Moffitt
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Marginal Treatment Effects and Monotonicity
How robust are analyses based on marginal treatment effects (MTE) to violations of Imbens and Angrist (1994) monotonicity? In this note, I present weaker forms of monotonicity under which popular MTE-based estimands still identify the parameters of interest.
Sigstad, Henrik
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Identifying marginal treatment effects in the presence of sample selection [PDF]
Journal of Econometrics, 2021 To be published in the Journal of ...
Kedagni, Desire +2 more
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The neutrality of taxation of investment projects in Serbia [PDF]
Ekonomski Anali, 2021 The paper analyses the neutrality of taxation of investment projects on the example of Serbia. The aim of the research is to confirm/reject the existence of uniformity of the tax burden on investment projects that differ regarding the asset type,
Luković Stevan +3 more
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Conformal Sensitivity Analysis for Individual Treatment Effects [PDF]
Journal of the American Statistical Association, 2021 Estimating an individual treatment effect (ITE) is essential to personalized decision making. However, existing methods for estimating the ITE often rely on unconfoundedness, an assumption that is fundamentally untestable with observed data.
Mingzhang Yin +3 more
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Pre-apprenticeship training for young people: Estimating the marginal and average treatment effects [PDF]
, 2022 This paper evaluates traineeships, a voluntary programme of work placement and preparation that aims to help young unemployed people in England compete for jobs and apprenticeships.
Stokes, L., Dorsett, R.
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More is exponentially less: marginal utility in critical care research
Journal of Evidence-Based Healthcare, 2022 BACKGROUND: Randomized clinical trials (RCT) in critical care mostly return negative results. The research community discusses strategies to improve RCTs design.
Rafael Olivé Leite
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Conflating marginal and conditional treatment effects: Comments on “Assessing the performance of population adjustment methods for anchored indirect comparisons: A simulation study” [PDF]
Statistics in Medicine, 2020 In this commentary, we highlight the importance of: (1) carefully considering and clarifying whether a marginal or conditional treatment effect is of interest in a population‐adjusted indirect treatment comparison; and (2) developing distinct ...
Antonio Remiro-Azócar +2 more
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Model-Assisted Inference for Covariate-Specific Treatment Effects with High-dimensional Data [PDF]
Statistica sinica, 2021 Covariate-specific treatment effects (CSTEs) represent heterogeneous treatment effects across subpopulations defined by certain selected covariates. In this article, we consider marginal structural models where CSTEs are linearly represented using a set ...
Peng Wu +3 more
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