A note on hypothesis testing in LAV multiple regression: A small sample comparison

We compare three approaches for assessing the significance of coefficients in least absolute value (LAV) multiple regression. The three test procedures studied are the Wald, likelihood ratio (LR), and Lagrange multiplier (LM) tests. Empirical levels of significance and power for the three test procedures are compared based on Monte Carlo simulation. This paper extends previous studies that concentrated only on simple regression. Further, the performance of overall goodness-of-fit tests for multiple regression is also examined, and a more extensive examination of the power of the tests is performed. The results of the study suggest that the LR and LM tests are preferable to the Wald test for this situation.