483 citations · 1.3k across the 30 of their papers we have counts for
20 papers · 1 filter
Apportioning Causal Responsibility of Two Risk Factors for an Adverse Outcome via Counterfactual Attribution
Shanshan Luo, Yafang Deng, Qingyuan Zhao +1
Unlike traditional causal inference, which prospectively evaluates the effects of causes, apportioning causal responsibility requires a retrospective assessment to deduce the cause…
Simultaneous false discovery rate control in location families
Zijun Gao, Wenjie Hu, Qingyuan Zhao
When testing a number of statistical hypotheses using data from location families, it is often useful to control the false discovery rate (FDR) not just for hypotheses of the null…
Simultaneous Hypothesis Testing Using Internal Negative Controls with An Application to Proteomics
Zijun Gao, Qingyuan Zhao
Negative control is a common technique in scientific investigations and broadly refers to the situation where a null effect (''negative result'') is expected. Motivated by a real p…
Optimization-based Sensitivity Analysis for Unmeasured Confounding using Partial Correlations
Tobias Freidling, Qingyuan Zhao
Causal inference necessarily relies upon untestable assumptions; hence, it is crucial to assess the robustness of obtained results to violations of identification assumptions. Howe…
An average-case sensitivity analysis for unmeasured confounding
Yao Zhang, Qingyuan Zhao
Sensitivity analysis for the unconfoundedness assumption is crucial in observational studies. For this purpose, the marginal sensitivity model gained popularity recently due to goo…
A unified analysis of regression adjustment in randomized experiments
Katarzyna Reluga, Ting Ye, Qingyuan Zhao
Regression adjustment is broadly applied in randomized trials under the premise that it usually improves the precision of a treatment effect estimator. However, previous work has s…
Almost exact Mendelian randomization
Matthew J Tudball, George Davey Smith, Qingyuan Zhao
Mendelian randomization (MR) is a natural experimental design based on the random transmission of genes from parents to offspring. However, this inferential basis is typically only…
Confounder Selection: Objectives and Approaches
F. Richard Guo, Anton Rask Lundborg, Qingyuan Zhao
Confounder selection is perhaps the most important step in the design of observational studies. A number of criteria, often with different objectives and approaches, have been prop…
What is a randomization test?
Yao Zhang, Qingyuan Zhao
The meaning of randomization tests has become obscure in statistics education and practice over the last century. This article makes a fresh attempt at rectifying this core concept…
Toward Better Practice of Covariate Adjustment in Analyzing Randomized Clinical Trials
Ting Ye, Jun Shao, Yanyao Yi +1
In randomized clinical trials, adjustments for baseline covariates at both design and analysis stages are highly encouraged by regulatory agencies. A recent trend is to use a model…
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…
Sample-constrained partial identification with application to selection bias
Matthew Tudball, Rachael Hughes, Kate Tilling +2
Many partial identification problems can be characterized by the optimal value of a function over a set where both the function and set need to be estimated by empirical data. Desp…
Sensitivity analysis for inverse probability weighting estimators via the percentile bootstrap
Qingyuan Zhao, Dylan S. Small, Bhaswar B. Bhattacharya
To identify the estimand in missing data problems and observational studies, it is common to base the statistical estimation on the "missing at random" and "no unmeasured confounde…
Selective inference for effect modification via the lasso
Qingyuan Zhao, Dylan S. Small, Ashkan Ertefaie
Effect modification occurs when the effect of the treatment on an outcome varies according to the level of other covariates and often has important implications in decision making.…
Cross-screening in observational studies that test many hypotheses
Qingyuan Zhao, Dylan S. Small, Paul R. Rosenbaum
We discuss observational studies that test many causal hypotheses, either hypotheses about many outcomes or many treatments. To be credible an observational study that tests many c…
Multiple testing when many -values are uniformly conservative, with application to testing qualitative interaction in educational interventions
Qingyuan Zhao, Dylan S. Small, Weijie Su
In the evaluation of treatment effects, it is of major policy interest to know if the treatment is beneficial for some and harmful for others, a phenomenon known as qualitative int…
On sensitivity value of pair-matched observational studies
Qingyuan Zhao
An observational study may be biased for estimating causal effects by failing to control for unmeasured confounders. This paper proposes a new quantity called the "sensitivity valu…
Covariate Balancing Propensity Score by Tailored Loss Functions
Qingyuan Zhao
In observational studies, propensity scores are commonly estimated by maxi- mum likelihood but may fail to balance high-dimensional pre-treatment covariates even after specificatio…
Confounder Adjustment in Multiple Hypothesis Testing
Jingshu Wang, Qingyuan Zhao, Trevor Hastie +1
We consider large-scale studies in which thousands of significance tests are performed simultaneously. In some of these studies, the multiple testing procedure can be severely bias…
Entropy balancing is doubly robust
Qingyuan Zhao, Daniel Percival
Covariate balance is a conventional key diagnostic for methods used estimating causal effects from observational studies. Recently, there is an emerging interest in directly incorp…