Cognitive: Define heterogeneity of treatment effect (HTE) and distinguish it from random variability; Describe different types of HTE analysis (e.g., confirmatory, exploratory); Recognize the importance of study design and pre-specification of the analysis plan; Distinguish between hypothesis testing and model-based estimation; Differentiate between statistical interaction and biological interaction; Understand the challenges of identifying HTE.
Attitudinal: Appreciate that patients may respond differently to treatments; Commit to the importance of evaluating HTE in PCOR.
Skills: Formulate a study design for detecting HTE (e.g., sample size with adequate power to detect HTE versus average treatment effect (ATE), pre-specification of subgroups); Select appropriate techniques for the evaluation of HTE (e.g., hypothesis testing, test of interaction, models of interaction, Bayesian modeling approaches); Demonstrate an understanding of statistical concepts for the evaluation of HTE (e.g., Type I and Type II errors, multiple testing, power, interactions); Use a software tool for conducting simple HTE analyses in a case study.
This category contains the curriculum Introduction and eight main modules. Learn about the instructors for this curriculum.
- Introductory Lecture: Prepared and presented by Jodi Segal, MD, MPH
- Learning Modules: Prepared and presented by Ravi Varadhan, PhD, and Chenguang Wang, PhD
Category 5 Self-Assessment
Back to the Methodology Standards Academic Curriculum main page
Posted: February 2016