A Multilevel Binary Logistic Regression Model of Success in Anatomy and Physiology I: A Retrospective Analysis

Abstract

Anatomy and physiology (AP) are subfields of biology that are gatekeeper courses for the health professions. This exploratory study used multilevel binary logistic regression to determine if age/gender and race/ethnicity were used as predictors of success, while the term offered and the identification number were specified as random effects. Two models were used. Those earning the grades of A, B and C were defined as successful for both models. Those earning the grades of D and F and those who withdrew (W) were defined as successful for one model, while the other model had the withdrawals removed. Ethnicity and gender predicted success in both models, with Native Americans and African Americans being less likely to succeed than Caucasians with the withdrawn students included. The model without withdrawn students was similar, except Hispanic students were also less likely to succeed than Caucasians. Females were more likely to succeed than males in both models. Efforts to retain equity in AP pedagogy should be prioritized.