Results 111 to 120 of about 4,712,566 (254)
Evaluating Treatment Prioritization Rules via Rank-Weighted Average Treatment Effects
Journal of the American Statistical AssociationThere are a number of available methods for selecting whom to prioritize for treatment, including ones based on treatment effect estimation, risk scoring, and hand-crafted rules. We propose rank-weighted average treatment effect (RATE) metrics as a simple and general family of metrics for comparing and testing the quality of treatment prioritization ...
Steve Yadlowsky +4 more
openaire +3 more sources
The newfound relationship between extrachromosomal DNAs and excised signal circles
FEBS Letters, EarlyView.Extrachromosomal DNAs (ecDNAs) contribute to the progression of many human cancers. In addition, circular DNA by‐products of V(D)J recombination, excised signal circles (ESCs), have roles in cancer progression but have largely been overlooked. In this Review, we explore the roles of ecDNAs and ESCs in cancer development, and highlight why these ...
Dylan Casey, Zeqian Gao, Joan Boyes
wiley +1 more source
Estimation of treatment effects with high-dimensional controls [PDF]
We propose methods for inference on the average effect of a treatment on a scalar outcome in the presence of very many controls. Our setting is a partially linear regression model containing the treatment/policy variable and a large number p of controls ...
Alexandre Belloni +2 more
core
BOUNDS ON THE CONDITIONAL AND AVERAGE TREATMENT EFFECT WITH UNOBSERVED CONFOUNDING FACTORS. [PDF]
Ann Stat, 2022 Yadlowsky S +4 more
europepmc +1 more source
FEBS Letters, EarlyView.Cryptochrome and PAS/LOV proteins play intricate roles in circadian clocks where they act as both sensors and mediators of protein–protein interactions. Their ubiquitous presence in signaling networks has positioned them as targets for small‐molecule therapeutics. This review provides a structural introduction to these protein families.
Eric D. Brinckman +2 more
wiley +1 more source
Identification of Treatment Effects Using Control Functions in Models with Continuous, Endogenous Treatment and Heterogeneous Effects [PDF]
We use the control function approach to identify the average treatment effect and the effect of treatment on the treated in models with a continuous endogenous regressor whose impact is heterogeneous.
C. Meghirx +3 more
core
Generalized coarsened confounding for causal effects: a large-sample framework
Journal of Causal InferenceThere has been widespread use of causal inference methods for the rigorous analysis of observational studies and to identify policy evaluations. In this article, we consider a class of generalized coarsened procedures for confounding.
Ghosh Debashis, Wang Lei
doaj +1 more source
Double Robust Bayesian Inference on Average Treatment Effects
EconometricaWe propose a double robust Bayesian inference procedure on the average treatment effect (ATE) under unconfoundedness. For our new Bayesian approach, we first adjust the prior distributions of the conditional mean functions, and then correct the posterior distribution of the resulting ATE.
Breunig, Christoph +2 more
openaire +4 more sources
FEBS Letters, EarlyView.This study reveals how the mitochondrial protein Slm35 is regulated in Saccharomyces cerevisiae. The authors identify stress‐responsive DNA elements and two upstream open reading frames (uORFs) in the 5′ untranslated region of SLM35. One uORF restricts translation, and its mutation increases Slm35 protein levels and mitophagy.
Hernán Romo‐Casanueva +5 more
wiley +1 more source
Program Evaluation and Random Program Starts [PDF]
This paper discusses the evaluation problem using observational data when the timing of treatment is an outcome of a stochastic process. We show that, without additional assumptions, it is not possible to estimate the average treatment effect and ...
Per Johansson, Peter Fredriksson
core