This is a preview. Log in through your library . Abstract We present a framework for generating multiple imputations for continuous data when the missing data mechanism is unknown. Imputations are ...

Missing data in clinical trials remains an ongoing concern. With the expansion of data privacy efforts and the consequent inability to contact trial participants for follow-up, the magnitude and ...

We derive information bounds for the regression parameters in Cox models when data are missing at random. These calculations are of interest for understanding the behavior of efficient estimation in ...

There are data about practically everything these days, and they can be used to try to answer any number of questions. Do clinical trials really show a drug works? Can surveys really signal who’s ...

At every stage of the Covid-19 pandemic, national reporting of racial and ethnic disparities in Covid-19 testing, diagnosis, disease severity, treatment, and vaccination by clinicians, public health ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Improving the robustness of machine learning (ML) models for natural ...