Related Experiment Video
Updated: May 1, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
Adjusting for misclassification in a stratified biomarker clinical trial
Chunling Liu1, Aiyi Liu, Jiang Hu
1Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China.
Abstract:
Clinical trials utilizing predictive biomarkers have become a research focus in personalized medicine. We investigate the effects of biomarker misclassification on the design and analysis of stratified biomarker clinical trials. For a variety of inference problems including marker-treatment interaction in particular, we show that marker misclassification may have profound adverse effects on the coverage of confidence intervals, power of the tests, and required sample sizes. For each inferential problem, we propose methods to adjust for the classification errors.
Related Concept Videos
Strategies for Assessing and Addressing Confounding
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
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,...
Blinding
Confounding in Epidemiological Studies
Bias in Epidemiological Studies
Clinical Trials
There are four phases in a clinical trial. A phase one...
