Robust estimation in the nested case-control design under a misspecified covariate functional form.

The Cox proportional hazards model is typically used to analyze time-to-event data. If the event of interest is rare and covariates are difficult or expensive to collect, the nested case-control (NCC) design provides consistent estimates at reduced costs with minimal impact on precision if the model is specified correctly. If our scientific goal is to conduct inference regarding an association of interest, it is essential that we specify the model a priori to avoid multiple testing bias. We cannot, however, be certain that all assumptions will be satisfied so it is important to consider robustness of the NCC design under model misspecification. In this manuscript, we show that in finite sample settings where the functional form of a covariate of interest is misspecified, the estimates resulting from the partial likelihood estimator under the NCC design depend on the number of controls sampled at each event time. To account for this dependency, we propose an estimator that recovers the results obtained using using the full cohort, where full covariate information is available for all study participants. We present the utility of our estimator using simulation studies and show the theoretical properties. We end by applying our estimator to motivating data from the Alzheimer's Disease Neuroimaging Initiative.

Optimal auxiliary-covariate-based two-phase sampling design for semiparametric efficient estimation of a mean or mean difference, with application to clinical trials.

To address the objective in a clinical trial to estimate the mean or mean difference of an expensive endpoint Y, one approach employs a two-phase sampling design, wherein inexpensive auxiliary variables W predictive of Y are measured in everyone, Y is measured in a random sample, and the semiparametric efficient estimator is applied. This approach is made efficient by specifying the phase two selection probabilities as optimal functions of the auxiliary variables and measurement costs. While this approach is familiar to survey samplers, it apparently has seldom been used in clinical trials, and several novel results practicable for clinical trials are developed. We perform simulations to identify settings where the optimal approach significantly improves efficiency compared to approaches in current practice. We provide proofs and R code. The optimality results are developed to design an HIV vaccine trial, with objective to compare the mean 'importance-weighted' breadth (Y) of the T-cell response between randomized vaccine groups. The trial collects an auxiliary response (W) highly predictive of Y and measures Y in the optimal subset. We show that the optimal design-estimation approach can confer anywhere between absent and large efficiency gain (up to 24 % in the examples) compared to the approach with the same efficient estimator but simple random sampling, where greater variability in the cost-standardized conditional variance of Y given W yields greater efficiency gains. Accurate estimation of E[Y | W] is important for realizing the efficiency gain, which is aided by an ample phase two sample and by using a robust fitting method.

Ultrasensitive and rapid colorimetric detection of urotropin boosted by effective electrostatic probing and non-covalent sampling.

Leakage and contamination of hazardous chemical substances have been widely recognized as the critical issue in ensuring human health, maintaining environmental sustainability, and safeguarding public security. Urotropin as a crucial raw material in industrial holds a potential threat to aquatic/atmospheric environment with refractory degradation problem, hence, there remains a severe challenge to effectively and on-site monitor urotropin. Here, a general design with all-in-one strategy was presented, in which a highly integrated "pocket sensing chip" combining a sampling unit and a detecting unit together endows a rapid and ultrasensitive colorimetric detection without dead-zone towards urotropin. By loading fast blue B as sensing reagent in the detecting unit, a moderate and sensitive detection towards urotropin via electrostatic interaction was achieved with detection limits of 9 µM for liquid and 17.19 ng for particulates. Furthermore, an expandable sensing chip for the purpose of simultaneously screening on multi-target exhibited remarkable applicability for examining suspicious objects with all sorts of surface in real scenes, being unacted on environmental complexity. We expect this design would provide a universal strategy and the high referential value to propel the development of handy and portable sensing device to efficiently screen the environmental relevant critical substance on-site.