A linear model has a few disadvantages:
-
A linear model is based on certain strong assumptions that may or may not hold true in practice. It takes into account a linear connection, multivariate normality, no or minimal multicollinearity, no autocorrelation, and homoscedasticity.
-
For discrete or binary outcomes, a linear model cannot be employed.
-
A linear model’s flexibility cannot be changed.