2 citations · 7 across the 8 of their papers we have counts for
8 papers
Controlling FDR in selecting group-level simultaneous signals from multiple data sources with application to the National Covid Collaborative Cohort data
Runqiu Wang, Ran Dai, Hongying Dai +2
One challenge in exploratory association studies using observational data is that the associations between the predictors and the outcome are potentially weak and rare, and the can…
FDR Controlled Multiple Testing for Union Null Hypotheses: A Knockoff-based Approach
Ran Dai, Cheng Zheng
False discovery rate (FDR) controlling procedures provide important statistical guarantees for the replicability in signal identification based on multiple hypotheses testing. In m…
Convergence guarantee for the sparse monotone single index model
Ran Dai, Hyebin Song, Rina Foygel Barber +1
We consider a high-dimensional monotone single index model (hdSIM), which is a semiparametric extension of a high-dimensional generalize linear model (hdGLM), where the link functi…
Post-selection inference on high-dimensional varying-coefficient quantile regression model
Ran Dai, Mladen Kolar
Quantile regression has been successfully used to study heterogeneous and heavy-tailed data. Varying-coefficient models are frequently used to capture changes in the effect of inpu…
Convex and Non-convex Approaches for Statistical Inference with Class-Conditional Noisy Labels
Hyebin Song, Ran Dai, Garvesh Raskutti +1
We study the problem of estimation and testing in logistic regression with class-conditional noise in the observed labels, which has an important implication in the Positive-Unlabe…
The bias of isotonic regression
Ran Dai, Hyebin Song, Rina Foygel Barber +1
We study the bias of the isotonic regression estimator. While there is extensive work characterizing the mean squared error of the isotonic regression estimator, relatively little…
On High Dimensional Covariate Adjustment for Estimating Causal Effects in Randomized Trials with Survival Outcomes
Ran Dai, Cheng Zheng, Mei-Jie Zhang
The purpose of this work is to improve the efficiency in estimating the average causal effect (ACE) on the survival scale where right-censoring exists and high-dimensional covariat…
Instrumental Variable with Competing Risk Model
Cheng Zheng, Ran Dai, Parameswaran Hari +1
In this paper, we discuss causal inference on the efficacy of a treatment or medication on a time-to-event outcome with competing risks. Although the treatment group can be randomi…