Statistical Methods for Standard Membrane-Feeding Assays to Measure Transmission Blocking or Reducing Activity in Malaria
衡量疟疾传播阻断或减少活性的标准膜饲喂试验统计方法AI 解读 ↓
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衡量疟疾传播阻断或减少活性的标准膜饲喂试验统计方法AI 解读 ↓
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Transmission blocking vaccines for malaria are not designed to directly protect vaccinated people from malaria disease, but to reduce the probability of infecting other people by interfering with the growth of the malaria parasite in mosquitoes. Standard membrane-feeding assays compare the growth of parasites in mosquitoes from a test sample (using antibodies from a vaccinated person) compared to a control sample. There is debate about whether to estimate the transmission reducing activity (TRA) which compares the mean number of parasites between test and control samples, or transmission blocking activity (TBA) which compares the proportion of infected mosquitoes. TBA appears biologically more important since each mosquito with any parasites is potentially infective; however, TBA is less reproducible and may be an overly strict criterion for screening vaccine candidates. Through a statistical model, we show that the TBA estimand depends on μc, the mean number of parasites in the control mosquitoes, a parameter not easily experimentally controlled. We develop a standardized TBA estimator based on the model and a given target value for μc which has better mean squared error than alternative methods. We discuss types of statistical inference needed for using these assays for vaccine development. Supplementary materials for this article are available online.
Background: Generalized Odds (Gen Odds) provide summaries for ordinal outcomes without requiring the proportional odds assumption. However, conventional Gen Odds compares independently drawn treatment and control outcomes and targets a population-level contrast rather than an individual-level contrast. We developed an individual-level causal formulation of Gen Odds and examined its identification. Methods: We defined the Causal Gen Odds using the joint distribution of…
We develop a semiparametric continuous time inferential framework for testing cumulative treatment effects, including both immediate and carryover effects. The latent state process is modeled by an ordinary differential equation (ODE) whose drift depends on state and treatment, while the observed data are noisy measurements of this latent state at irregular, multi resolution time points. We define the average treatment effect (ATE) as the difference of expected cumulative…
Joint-event forecasts combine an estimated dependence model with current marginal forecasts. Retaining historical transforms at the marginal fits available when each outcome arrived creates overlapping estimation errors. We derive their joint influence with the terminal estimates in a stable Vine Copula VAR with normal innovation margins and a fixed, correctly specified Gaussian or positive Clayton vine. An intercept identity and the stable VAR filter reduce the historical…
We study inference for continuous linear functionals of solutions to ill-posed inverse problems, including Euclidean parameters arising in nonparametric instrumental variables, proximal causal inference, and shadow-variable models. Although pointwise root-$n$ inference is possible under standard conditions, we show that this need not translate into locally reliable inference. Under a model imposing only minimal regularity conditions, the target is Hellinger discontinuous…
近端估计与推断
Abstract We develop a convex-analytic framework for constructing and analyzing a broad class of penalized estimators. Our method defines penalized estimators by applying proximal operators to benchmark estimators, rather than by penalizing the benchmark criterion itself. We establish general finite-sample properties, derive unified asymptotic distribution results, and provide tractable conditions for oracle selection and oracle asymptotic efficiency. We then apply the…
多因子线性资产定价模型 GMM 估计中的效率与定价精度权衡
Even though a multi-factor linear asset pricing model can be equivalently represented in a Beta or in a stochastic discount factor (SDF) form, its inferential efficiency and pricing accuracy features may differ when estimated by the generalized method of moments (GMM), both in small and in large samples. We derive the analytical asymptotic variance of the Beta and the SDF estimators under GMM and find that the SDF approach is likely to be less efficient but to yield more…