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03/17/2023
Proximal Causal Inference without Uniqueness Assumptions
We consider identification and inference about a counterfactual outcome ...
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10/05/2022
Doubly Robust Proximal Synthetic Controls
To infer the treatment effect for a single treated unit using panel data...
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10/01/2022
Paradoxes and resolutions for semiparametric fusion of individual and summary data
Suppose we have available individual data from an internal study and var...
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08/02/2022
Doubly Robust Proximal Causal Inference under Confounded Outcome-Dependent Sampling
Unmeasured confounding and selection bias are often of concern in observ...
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07/18/2022
A self-censoring model for multivariate nonignorable nonmonotone missing data
We introduce a self-censoring model for multivariate nonignorable nonmon...
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06/16/2022
Identification and estimation of causal effects in the presence of confounded principal strata
The principal stratification has become a popular tool to address a broa...
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03/23/2022
Double Negative Control Inference in Test-Negative Design Studies of Vaccine Effectiveness
The test-negative design (TND) has become a standard approach to evaluat...
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12/06/2021
A stableness of resistance model for nonresponse adjustment with callback data
The survey world is rife with nonresponse and in many situations the mis...
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10/12/2021
Identification and estimation of nonignorable missing outcome mean without identifying the full data distribution
We consider the problem of making inference about the population outcome...
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10/03/2021
Data Integration in Causal Inference
Integrating data from multiple heterogeneous sources has become increasi...
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09/15/2021
Proximal Causal Inference for Complex Longitudinal Studies
A standard assumption for causal inference about the joint effects of ti...
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08/31/2021
Theory for identification and Inference with Synthetic Controls: A Proximal Causal Inference Framework
Synthetic control methods are commonly used to estimate the treatment ef...
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08/28/2021
A robust fusion-extraction procedure with summary statistics in the presence of biased sources
Information from various data sources is increasingly available nowadays...
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06/28/2021
Evolutionary Multi-Objective Virtual Network Function Placement: A Formal Model and Effective Algorithms
Data centers are critical to the commercial and social activities of mod...
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11/19/2020
Sharp bounds for variance of treatment effect estimators in the finite population in the presence of covariates
In the completely randomized experiment, the variances of treatment effe...
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11/17/2020
Semiparametric proximal causal inference
Skepticism about the assumption of no unmeasured confounding, also known...
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11/14/2020
Improving efficiency of inference in clinical trials with external control data
Suppose we are interested in the effect of a treatment in a clinical tri...
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11/09/2020
Identifying effects of multiple treatments in the presence of unmeasured confounding
Identification of treatment effects in the presence of unmeasured confou...
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09/23/2020
An Introduction to Proximal Causal Learning
A standard assumption for causal inference from observational data is th...
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09/11/2020
A Selective Review of Negative Control Methods in Epidemiology
Purpose of Review: Negative controls are a powerful tool to detect and a...
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01/30/2020
Routing-Led Placement of VNFs in Arbitrary Networks
The ever increasing demand for computing resources has led to the creati...
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08/15/2018
A Confounding Bridge Approach for Double Negative Control Inference on Causal Effects (Supplement and Sample Codes are included)
Unmeasured confounding is a key challenge for causal inference. Negative...
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08/15/2018
A Confounding Bridge Approach for Double Negative Control Inference on Causal Effects
Unmeasured confounding is a key challenge for causal inference. Negative...
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08/14/2018
