8 citations · 9 across the 6 of their papers we have counts for
6 papers
How should we select test-negative controls? A causal perspective in the era of multiplex respiratory testing
Christopher B. Boyer, Kendrick Qijun Li, Xu Shi +2
The test-negative design (TND) is widely used to estimate vaccine effectiveness (VE) for respiratory pathogens by comparing vaccination odds among test-positive cases versus test-n…
Test-negative designs with various reasons for testing: statistical bias and solution
Mengxin Yu, Tom Hongyi Liu, Kendrick Qijun Li +5
Test-negative designs are widely used for post-market evaluation of vaccine effectiveness, particularly in cases when randomized trials are not feasible. Differing from classical t…
Doubly Robust Proximal Causal Inference under Confounded Outcome-Dependent Sampling
Kendrick Qijun Li, Xu Shi, Wang Miao +1
Unmeasured confounding and selection bias are often of concern in observational studies and may invalidate a causal analysis if not appropriately accounted for. Under outcome-depen…
A Bayesian 'sandwich' for variance estimation
Kendrick Qijun Li, Kenneth Martin Rice
Large-sample Bayesian analogs exist for many frequentist methods, but are less well-known for the widely-used 'sandwich' or 'robust' variance estimates. We review existing approach…
Double Negative Control Inference in Test-Negative Design Studies of Vaccine Effectiveness
Kendrick Qijun Li, Xu Shi, Wang Miao +1
The test-negative design (TND) has become a standard approach to evaluate vaccine effectiveness against the risk of acquiring infectious diseases in real-world settings, such as In…
Theory for identification and Inference with Synthetic Controls: A Proximal Causal Inference Framework
Xu Shi, Kendrick Li, Wang Miao +2
Synthetic control (SC) methods are commonly used to estimate the treatment effect on a single treated unit in panel data settings. An SC is a weighted average of control units buil…