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20182021
most citedMinimax Rates and Adaptivity in Combining Experimental and Observational Data

5 citations · 7 across the 2 of their papers we have counts for

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5 papers · 1 filter

stat.ME20215 cited

Minimax Rates and Adaptivity in Combining Experimental and Observational Data

Shuxiao Chen, Bo Zhang, Ting Ye

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 generali…

stat.ME2021

Estimating and Improving Dynamic Treatment Regimes With a Time-Varying Instrumental Variable

Shuxiao Chen, Bo Zhang

Estimating dynamic treatment regimes (DTRs) from retrospective observational data is challenging as some degree of unmeasured confounding is often expected. In this work, we develo…

stat.ME2020

Selecting and ranking individualized treatment rules with unmeasured confounding

Bo Zhang, Jordan Weiss, Dylan S Small +1

It is common to compare individualized treatment rules based on the value function, which is the expected potential outcome under the treatment rule. Although the value function is…

stat.ME2020

Estimating Optimal Treatment Rules with an Instrumental Variable: A Partial Identification Learning Approach

Hongming Pu, Bo Zhang

Individualized treatment rules (ITRs) are considered a promising recipe to deliver better policy interventions. One key ingredient in optimal ITR estimation problems is to estimate…

stat.ME2018

A calibrated sensitivity analysis for matched observational studies with application to the effect of second-hand smoke exposure on blood lead levels in U.S. children

Bo Zhang, Dylan Small

Matched observational studies are commonly used to study treatment effects in non-randomized data. After matching for observed confounders, there could remain bias from unobserved…