Life tables with concomitant information

A regression model for the analysis of survival data adjusting for concomitant information is developed. The model presented can lead to the log linear exponential model (Glasser [1967]) and the life table regression model of Cox [1972]. In addition, the model described can be used to analyze data from the commonly employed actuarial life table. A discussion of the special case where one is comparing two survival curves is presented. The methods developed are illustrated using data from a clinical trial investigating treatments for lung cancer.     

Statistical evaluation of the role of Helicobacter pylori in stress gastritis: applications of splines and bootstrapping to the logistic model

Stress gastritis is a serious problem in the intensive care unit population. The recent discovery of the causal nature of Helicobacter pylori (H. pylori) in the development of gastric ulcers led us to examine its relationship with stress gastritis. We investigated this relationship in 874 veterans admitted to intensive care units who were tested for the presence of H. pylori and followed for 6 weeks for the development of stress gastritis. We fit spline models to assess functional relationships and used the logistic model to determine the association between H. pylori and stress gastritis. The predictive ability of the model was assessed with receiver operating characteristic (ROC) curve analysis and validated with the bootstrapping technique. Increased anti-H. pylori immunoglobulin A concentrations were found to be an important predictor of stress gastritis independent of other known risk factors.