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07/21/2023
Multiple bias-calibration for adjusting selection bias of non-probability samples using data integration
Valid statistical inference is challenging when the sample is subject to...
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07/10/2023
Enhancing Treatment Effect Estimation: A Model Robust Approach Integrating Randomized Experiments and External Controls using the Double Penalty Integration Estimator
Randomized experiments (REs) are the cornerstone for treatment effect ev...
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06/29/2023
Integrating Randomized Placebo-Controlled Trial Data with External Controls: A Semiparametric Approach with Selective Borrowing
In recent years, real-world external controls (ECs) have grown in popula...
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05/28/2023
Pretest estimation in combining probability and non-probability samples
Multiple heterogeneous data sources are becoming increasingly available ...
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05/23/2023
Augmented match weighted estimators for average treatment effects
Propensity score matching (PSM) and augmented inverse propensity weighti...
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04/18/2023
Quadruply robust estimation of marginal structural models in observational studies subject to covariate-driven observations
Electronic health records and other sources of observational data are in...
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04/04/2023
Is ChatGPT a Highly Fluent Grammatical Error Correction System? A Comprehensive Evaluation
ChatGPT, a large-scale language model based on the advanced GPT-3.5 arch...
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01/26/2023
Variable Selection for Doubly Robust Causal Inference
Confounding control is crucial and yet challenging for causal inference ...
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01/13/2023
Efficient and robust transfer learning of optimal individualized treatment regimes with right-censored survival data
An individualized treatment regime (ITR) is a decision rule that assigns...
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11/03/2022
A Bayesian Semiparametric Method For Estimating Causal Quantile Effects
Standard causal inference characterizes treatment effect through average...
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10/28/2022
Ultra-fast, programmable, and electronics-free soft robots enabled by snapping metacaps
Soft robots have a myriad of potentials because of their intrinsically c...
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10/08/2022
Matching Estimators of Causal Effects in Clustered Observational Studies with Application to Quantifying the Impact of Marine Protected Areas on Biodiversity
Marine conservation preserves fish biodiversity, protects marine and coa...
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10/05/2022
Transporting survival of an HIV clinical trial to the external target populations
Due to the heterogeneity of the randomized controlled trial (RCT) and ex...
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09/26/2022
Self-supervised Denoising via Low-rank Tensor Approximated Convolutional Neural Network
Noise is ubiquitous during image acquisition. Sufficient denoising is of...
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09/23/2022
Faith: An Efficient Framework for Transformer Verification on GPUs
Transformer verification draws increasing attention in machine learning ...
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08/01/2022
Towards R-learner of conditional average treatment effects with a continuous treatment: T-identification, estimation, and inference
The R-learner has been popular in causal inference as a flexible and eff...
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06/02/2022
Soft calibration for selection bias problems under mixed-effects models
Calibration weighting has been widely used for correcting selection bias...
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05/24/2022
UMSNet: An Universal Multi-sensor Network for Human Activity Recognition
Human activity recognition (HAR) based on multimodal sensors has become ...
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04/25/2022
Trials with Irregular and Informative Assessment Times: A Sensitivity Analysis Approach
Many trials are designed to collect outcomes at pre-specified times afte...
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04/23/2022
When Doubly Robust Methods Meet Machine Learning for Estimating Treatment Effects from Real-World Data: A Comparative Study
Observational cohort studies are increasingly being used for comparative...
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03/28/2022
Functional principal component analysis for longitudinal observations with sampling at random
Functional principal component analysis has been shown to be invaluable ...
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03/20/2022
Robust analyses for longitudinal clinical trials with missing and non-normal continuous outcomes
Missing data is unavoidable in longitudinal clinical trials, and outcome...
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03/17/2022
Sensitivity analysis in longitudinal clinical trials via distributional imputation
Missing data is inevitable in longitudinal clinical trials. Conventional...
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02/23/2022
Nearest neighbor ratio imputation with incomplete multi-nomial outcome in survey sampling
Nonresponse is a common problem in survey sampling. Appropriate treatmen...
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01/17/2022
Generalizable survival analysis of randomized controlled trials with observational studies
In the presence of heterogeneity between the randomized controlled trial...
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01/17/2022
Targeted Optimal Treatment Regime Learning Using Summary Statistics
Personalized decision-making, aiming to derive optimal individualized tr...
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12/11/2021
Multiply robust estimators in longitudinal studies with missing data under control-based imputation
Longitudinal studies are often subject to missing data. The ICH E9(R1) a...
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08/19/2021
Transfer learning of individualized treatment rules from experimental to real-world data
Individualized treatment effect lies at the heart of precision medicine....
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07/26/2021
Outcome-Adjusted Balance Measure for Generalized Propensity Score Model Selection
In this article, we propose the outcome-adjusted balance measure to perf...
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03/07/2021
Estimating intervention effects on infectious disease control: the effect of community mobility reduction on Coronavirus spread
Understanding the effects of interventions, such as restrictions on comm...
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03/05/2021
Estimation of Partially Conditional Average Treatment Effect by Hybrid Kernel-covariate Balancing
We study nonparametric estimation for the partially conditional average ...
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02/27/2021
Instrumental variables, spatial confounding and interference
Unobserved spatial confounding variables are prevalent in environmental ...
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12/22/2020
A spectral adjustment for spatial confounding
Adjusting for an unmeasured confounder is generally an intractable probl...
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12/03/2020
Multiply robust estimation of causal effects under principal ignorability
Causal inference concerns not only the average effect of the treatment o...
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11/16/2020
Causal inference methods for combining randomized trials and observational studies: a review
With increasing data availability, treatment causal effects can be evalu...
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10/26/2020
A Distributed Training Algorithm of Generative Adversarial Networks with Quantized Gradients
Training generative adversarial networks (GAN) in a distributed fashion ...
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08/30/2020
Robust inference of conditional average treatment effects using dimension reduction
It is important to make robust inference of the conditional average trea...
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07/25/2020
Improved Inference for Heterogeneous Treatment Effects Using Real-World Data Subject to Hidden Confounding
The heterogeneity of treatment effect (HTE) lies at the heart of precisi...
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07/09/2020
SGQuant: Squeezing the Last Bit on Graph Neural Networks with Specialized Quantization
With the increasing popularity of graph-based learning, Graph Neural Net...
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07/06/2020
A review of spatial causal inference methods for environmental and epidemiological applications
The scientific rigor and computational methods of causal inference have ...
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07/05/2020
SMIM: a unified framework of Survival sensitivity analysis using Multiple Imputation and Martingale
Censored survival data are common in clinical trial studies. We propose ...
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06/30/2020
Generalized propensity score approach to causal inference with spatial interference
Many spatial phenomena exhibit treatment interference where treatments a...
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05/25/2020
Spatially varying causal effect models
We establish causal effect models that allow for time- and spatially var...
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05/21/2020
Elastic Integrative Analysis of Randomized Trial and Real-World Data for Treatment Heterogeneity Estimation
Parallel randomized trial (RT) and real-world (RW) data are becoming inc...
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03/12/2020
A spatial causal analysis of wildland fire-contributed PM2.5 using numerical model output
Wildland fire smoke contains hazardous levels of fine particulate matter...
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03/02/2020
Integrative analysis of randomized clinical trials with real world evidence studies
We leverage the complementing features of randomized clinical trials (RC...
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01/16/2020
Double score matching estimators of average and quantile treatment effects
Propensity score matching has a long tradition for handling confounding ...
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01/09/2020
Statistical Data Integration in Survey Sampling: A Review
Finite population inference is a central goal in survey sampling. Probab...
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11/27/2019
Causal inference of hazard ratio based on propensity score matching
Propensity score matching is commonly used to draw causal inference from...
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11/12/2019