108 – Teaching and Learning Applied Regression: Perspectives from Teachers and Students
Teaching and Learning Confounding in the Health Sciences
Rickey Carter
Mayo Clinic
Felicity Enders
Mayo Clinic
Miranda Kroehl
University of Colorado at Denver
John McGready
The Johns Hopkins University
In order to read or publish in the medical research literature, students in the health sciences need a thorough understanding of confounding. However, research shows that confounding may be poorly understood by some students even after two courses in biostatistics at the graduate level. We introduce two problem-based guided examples to increase both the breadth and depth of students' understanding of this challenging subject. The first is a visual introduction to confounding and interaction in which students naturally lead the discussion through a set of increasingly complex models. The second example links the analysis to study design and compares results for a t test, a t test performed within the context of regression, and an adjusted analysis termed an "adjusted t test" to help link understanding. We also identify topics for improved teaching for such a challenging subject as confounding, with the goal of removing barriers to student understanding.
