Multicollinearity can lead to several issues in epidemiological studies:
Unreliable Estimates: The standard errors of the coefficients can be inflated, leading to wide confidence intervals and unreliable estimates. Difficulty in Assessing Individual Predictor Effects: It becomes challenging to assess the individual effect of each predictor variable because of their high correlation. Model Interpretability: The interpretability of the model decreases, making it difficult to draw meaningful conclusions.
