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stat.ME2022
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…
stat.ME2022
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…
stat.ME2022
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…