In cancer research, multicollinearity can hinder the identification of risk factors and the development of predictive models. When multiple variables, such as genetic markers, lifestyle factors, and environmental exposures, are highly correlated, it becomes difficult to determine their individual contributions to cancer risk. This can lead to unreliable estimates and potentially incorrect conclusions.
