Results 151 to 160 of about 575,970 (287)
Rank‐based estimation of propensity score weights via subclassification
Abstract Propensity score (PS) weighting estimators are widely used for causal effect estimation and enjoy desirable theoretical properties, such as consistency and potential efficiency under correct model specification. However, their performance can degrade in practice due to sensitivity to PS model misspecification.
Linbo Wang +3 more
wiley +1 more source
Low-Latency Realism Through Randomized Distributed Function Computations: A Shannon Theoretic Approach. [PDF]
Günlü O, Skorski M, Poor HV.
europepmc +1 more source
Predicting cervical cancer DNA methylation from genetic data using multivariate CMMP
Abstract Epigenetic modifications link the environment to gene expression and play a crucial role in tumour development. DNA methylation, in particular, is gaining attention in cancer research, including cervical cancer, the focus of this study.
Hang Zhang +5 more
wiley +1 more source
Testing for Sufficient Follow-Up in Survival Data With a Cure Fraction. [PDF]
Yuen TP, Musta E.
europepmc +1 more source
Abstract We establish the consistency and the asymptotic distribution of the least squares estimators of the coefficients of a subset vector autoregressive process with exogenous variables (VARX). Using a martingale central limit theorem, we derive the asymptotic normal distribution of the estimators. Diagnostic checking is discussed using kernel‐based
Pierre Duchesne +2 more
wiley +1 more source
Asymptotic properties of cross‐classified sampling designs
Abstract We investigate the family of cross‐classified sampling designs across an arbitrary number of dimensions. We introduce a variance decomposition that enables the derivation of general asymptotic properties for these designs and the development of straightforward and asymptotically unbiased variance estimators.
Jean Rubin, Guillaume Chauvet
wiley +1 more source
Bayesian inverse ensemble forecasting for COVID‐19
Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
wiley +1 more source
A goodness‐of‐fit test for regression models with discrete outcomes
Abstract Regression models are often used to analyze discrete outcomes, but classical goodness‐of‐fit tests such as those based on the deviance or Pearson's statistic can be misleading or have little power in this context. To address this issue, we propose a new test, inspired by the work of Czado et al.
Lu Yang +2 more
wiley +1 more source
Powering RCTs for Marginal Effects With GLMs Using Prognostic Score Adjustment. [PDF]
Højbjerre-Frandsen E +2 more
europepmc +1 more source
A partial envelope approach for modelling multivariate spatial‐temporal data
Abstract In the new era of big data, modelling multivariate spatial‐temporal data is a challenging task due to both the high dimensionality of the features and complex associations among the responses across different locations and time points.
Reisa Widjaja +3 more
wiley +1 more source

