Related Experiment Video
Updated: Oct 11, 2025

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
Published on: October 25, 2011
Testing for heterogeneity in the utility of a surrogate marker
Layla Parast1, Tianxi Cai2, Lu Tian3
1Statistics Group, RAND Corporation, Santa Monica, California, USA.
Abstract:
In studies that require long-term and/or costly follow-up of participants to evaluate a treatment, there is often interest in identifying and using a surrogate marker to evaluate the treatment effect. While several statistical methods have been proposed to evaluate potential surrogate markers, available methods generally do not account for or address the potential for a surrogate to vary in utility or strength by patient characteristics. Previous work examining surrogate markers has indicated that there may be such heterogeneity, that is, that a surrogate marker may be useful (with respect to capturing the treatment effect on the primary outcome) for some subgroups, but not for others. This heterogeneity is important to understand, particularly if the surrogate is to be used in a future trial to replace the primary outcome. In this paper, we propose an approach and estimation procedures to measure the surrogate strength as a function of a baseline covariate W and thus examine potential heterogeneity in the utility of the surrogate marker with respect to W. Within a potential outcome framework, we quantify the surrogate strength/utility using the proportion of treatment effect on the primary outcome that is explained by the treatment effect on the surrogate. We propose testing procedures to test for evidence of heterogeneity, examine finite sample performance of these methods via simulation, and illustrate the methods using AIDS clinical trial data.
More Related Videos
13:19Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
11:34Building Up a High-throughput Screening Platform to Assess the Heterogeneity of HER2 Gene Amplification in Breast Cancers
Published on: December 5, 2017
Related Concept Videos
Test for Homogeneity
Comparing the Survival Analysis of Two or More Groups
Quantifying and Rejecting Outliers: The Grubbs Test
Kruskal-Wallis Test
Significance Testing: Overview
Statistical Methods to Analyze Parametric Data: Student t-Test and Goodness-of-Fit Test
The Student's t-test is a statistical test that examines if there is a statistically significant difference between the means of two groups. This test is instrumental when dealing with...