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How should we select test-negative controls? A causal perspective in the era of multiplex respiratory testing

多重呼吸道检测时代如何选择检测阴性对照:因果视角

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-negative controls. A central yet underexplored design element is which test-negative illnesses constitute valid controls. With rapid multiplex PCR panels, investigators can now identify specific non-focal pathogens among test-negative patients, allowing for better characterization of ``test-negative…

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Test-negative designs with various reasons for testing: statistical bias and solution

多种检测原因下的检测阴性设计:统计偏差与解决方法

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 test-negative designs where only healthcare-seekers with symptoms are included, recent test-negative designs have involved individuals with various reasons for testing, especially in an outbreak setting. While including these data can increase sample size and hence improve precision, concerns have…

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Doubly Robust Proximal Causal Inference under Confounded Outcome-Dependent Sampling

混杂性结局依赖抽样下的双重稳健近端因果推断

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-dependent sampling, a latent factor that has causal effects on the treatment, outcome, and sample selection process may cause both unmeasured confounding and selection bias, rendering standard causal parameters unidentifiable without additional assumptions. Under an odds ratio model for the treatment…

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