Results 71 to 80 of about 157 (97)

Minimax rates and adaptivity in combining experimental and observational data

Journal of Causal Inference
Randomized controlled trials (RCTs) are the gold standard for evaluating the causal effect of a treatment; however, they often have limited sample sizes and sometimes poor generalizability.
Chen Shuxiao, Li Sai, Zhang Bo, Ye Ting
doaj   +1 more source

Evaluating sensitivity to classification uncertainty in latent subgroup effect analyses. [PDF]

BMC Med Res Methodol, 2022
Loh WW, Kim JS.
europepmc   +1 more source

Geodesic Causal Inference

Adjusting for confounding and imbalance when establishing statistical relationships is an increasingly important task, and causal inference methods have emerged as the most popular tool to achieve this.
Kurisu, Daisuke, Müller, Hans-Georg, Otsu, Taisuke, Zhou, Yidong   +3 more
core  

Nonparametric estimation of conditional incremental effects

Journal of Causal Inference
Conditional effect estimation has great scientific and policy importance because interventions may impact subjects differently depending on their characteristics.
McClean Alec, Branson Zach, Kennedy Edward H.   +2 more
doaj   +1 more source

Identifying Total Causal Effects in Linear Models under Partial Homoscedasticity

A fundamental challenge of scientific research is inferring causal relations based on observed data. One commonly used approach involves utilizing structural causal models that postulate noisy functional relations among interacting variables.
Drton, Mathias, Strieder, David
core  

Doubly weighted M-estimation for nonrandom assignment and missing outcomes

Journal of Causal Inference
This article proposes a class of M-estimators that double weight for the joint problems of nonrandom treatment assignment and missing outcomes. Identification of the main parameter of interest is achieved under unconfoundedness and missing at random ...
Negi Akanksha
doaj   +1 more source

Goddard range and range rate system Design evaluation report [PDF]

Tracking and telemetry data at VHF and S band frequencies from spacecraft for GRARR ...

core   +1 more source

Synergy and Redundancy Measures: Theory and Applications to Characterize Complex Systems and Shape Neural Network Representations [PDF]

The following Special Issue covers advances in both the theoretical formulation and applications of information-theoretic measures of synergy and redundancy.

core  

Colored Gaussian DAG models

We study submodels of Gaussian DAG models defined by partial homogeneity constraints imposed on the model error variances and structural coefficients. We represent these models with colored DAGs and investigate their properties for use in statistical and
Boege, Tobias, Kubjas, Kaie, Misra, Pratik, Solus, Liam   +3 more
core  

Nonparametric Inference on Dose-Response Curves Without the Positivity Condition

Existing statistical methods in causal inference often rely on the assumption that every individual has some chance of receiving any treatment level regardless of its associated covariates, which is known as the positivity condition.
Chen, Yen-Chi, Giessing, Alexander, Zhang, Yikun   +2 more
core