Methods are devised for estimating the parameters of a prospective logistic model in a case{control study with dichotomous response D which depends on a covariate X. For a portion of the sample, both the gold standard X and a surrogate covariate W are available; however, for the greater portion of the data only the surrogate covariate W is available. By using a mixture model, the relationship b...

PURPOSE Competing risks observations, in which patients are subject to a number of potential failure events, are a feature of most clinical cancer studies. With competing risks, several modeling approaches are available to evaluate the relationship of covariates to cause-specific failures. We discuss the use and interpretation of commonly used competing risks regression models. EXPERIMENTAL D...

Three (3) different methods (logistic regression, covariate shift and k-NN) were applied to five (5) internal datasets and one (1) external, publically available dataset where covariate shift existed. In all cases, k-NN’s performance was inferior to either logistic regression or covariate shift. Surprisingly, there was no obvious advantage for using covariate shift to reweight the training data...

Reports of clinical trials often include adjusted analyses, which incorporate covariate data into the analysis model. Adjusting for covariates can increase the precision of treatment effect estimates and increase the power of statistical tests, without the need to increase sample size. In individually randomised trials, the main reason to adjust for a particular covariate is that it is expected...

Dataset shift is a problem widely studied in the field of speaker recognition. Among the different types of dataset shift, covariate shift is the most common one in real scenarios. Traditional solutions for the problem of covariate shift have been developed in the context of channel and session variability, and make use of large datasets to train models for channel/session compensation. However...

This paper describes CADFtest, a R (R Development Core Team 2008) package for testing for the presence of a unit root in a time series using the Covariate Augmented Dickey-Fuller (CADF) test proposed in Hansen (1995). The procedures presented here are user friendly, allow fully automatic model specification, and allow computation of the asymptotic p-values of the test.