Detecting assumption violations involves a combination of statistical tests, sensitivity analyses, and graphical methods. For example, residual plots can help detect violations of linearity, while tests for independence can identify correlated observations. Combining multiple diagnostic tools increases the likelihood of identifying and addressing assumption violations.
