In epidemiology, multicollinearity refers to a situation where two or more predictor variables in a multiple regression model are highly correlated. This means that one predictor variable can be linearly predicted from the others with a substantial degree of accuracy. It poses a significant problem because it can inflate the variance of the coefficient estimates and make the model unstable.
