Model adjustment in epidemiology refers to the process of including additional variables in a statistical model to control for confounding. Confounding occurs when an extraneous variable influences both the dependent variable and independent variable, leading to a spurious association. By adjusting for these confounders, researchers aim to isolate the effect of the primary exposure on the outcome.
