Zobrazeno 1 - 10
of 511 232
pro vyhledávání: '"Treatment effects"'
Testing Whether Reported Treatment Effects are Unduly Dependent on the Specific Outcome Measure Used
Autor:
Halpin, Peter, Gilbert, Joshua
This paper addresses the situation in which treatment effects are reported using educational or psychological outcome measures comprised of multiple questions or ``items.'' A distinction is made between a treatment effect on the construct being measu
Externí odkaz:
http://arxiv.org/abs/2409.03502
Randomized experiments are the gold standard for estimating treatment effects, yet network interference challenges the validity of traditional estimators by violating the stable unit treatment value assumption and introducing bias. While cluster rand
Externí odkaz:
http://arxiv.org/abs/2408.17205
Estimating the conditional average treatment effects (CATE) is very important in causal inference and has a wide range of applications across many fields. In the estimation process of CATE, the unconfoundedness assumption is typically required to ens
Externí odkaz:
http://arxiv.org/abs/2408.17053
Autor:
Guha, Sharmistha, Reiter, Jerome P.
In the social and health sciences, researchers often make causal inferences using sensitive variables. These researchers, as well as the data holders themselves, may be ethically and perhaps legally obligated to protect the confidentiality of study p
Externí odkaz:
http://arxiv.org/abs/2408.14766
Recently, from the personalized medicine perspective, there has been an increased demand to identify subgroups of subjects for whom treatment is effective. Consequently, the estimation of heterogeneous treatment effects (HTE) has been attracting atte
Externí odkaz:
http://arxiv.org/abs/2407.19659
We propose a novel regression adjustment method designed for estimating distributional treatment effect parameters in randomized experiments. Randomized experiments have been extensively used to estimate treatment effects in various scientific fields
Externí odkaz:
http://arxiv.org/abs/2407.16037
Autor:
Fava, Bruno
Important questions for impact evaluation require knowledge not only of average effects, but of the distribution of treatment effects. What proportion of people are harmed? Does a policy help many by a little? Or a few by a lot? The inability to obse
Externí odkaz:
http://arxiv.org/abs/2407.14635
In this paper, we address the issue of estimating and inferring the distributional treatment effects in randomized experiments. The distributional treatment effect provides a more comprehensive understanding of treatment effects by characterizing het
Externí odkaz:
http://arxiv.org/abs/2407.14074
Autor:
Chen, Zhe, Li, Xinran
Understanding treatment effect heterogeneity has become increasingly important in many fields. In this paper we study distributions and quantiles of individual treatment effects to provide a more comprehensive and robust understanding of treatment ef
Externí odkaz:
http://arxiv.org/abs/2407.13261