Related Experiment Video
Updated: May 28, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Joint modeling, covariate adjustment, and interaction: contrasting notions in risk prediction models and risk
Kathleen F Kerr1, Margaret S Pepe
1Department of Biostatistics and Fred Hutchinson Cancer Research Center, University of Washington, Seattle, WA 98195, USA. katiek@uw.edu
Abstract:
Epidemiologic methods are well established for investigating the association of a predictor of interest and disease status in the presence of covariates also associated with disease. There is less consensus on how to handle covariates when the goal is to evaluate the increment in prediction performance gained by a new marker when a set of predictors already exists. We distinguish between adjusting for covariates and joint modeling of disease risk in this context. We show that adjustment and joint modeling are distinct concepts, and we describe the specific conditions where they are the same. We also discuss the concept of interaction among variables and describe a notion of interaction that is relevant to prediction performance. We conclude with a discussion of the most appropriate methods for evaluating new biomarkers in the presence of existing predictors.
Related Concept Videos
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
The...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Mechanistic Models: Compartment Models in Individual and Population Analysis
Relative Risk
Assumptions of Survival Analysis
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time until a...
