As the coronavirus disease 2019 (COVID-19) pandemic has spread across the world, vast amounts of bioinformatics data have been created and analyzed, and logistic regression models have been key to ...

Logistic regression is a powerful technique for fitting models to data with a binary response variable, but the models are difficult to interpret if collinearity, nonlinearity, or interactions are ...

This study involved 3,708 patients with cancer, with an incidence of paclitaxel HSR of 10.11%. An 11-predictor–based Pac-HSR scoring system was developed, involving the following factors: younger age; ...

We present an approach for correcting for interobserver measurement error in an ordinal logistic regression model taking into account also the variability of the ...