Some robust procedures for comparing several straight lines under heteroscedasticity and non-normality

Abstract

In this paper we consider several straight lines and compare the regression coefficients under heteroscedastic variances. A test Fβ is proposed for this purpose by assuming normality for the random disturbances. Some Monte Carlo studies indicate that the Fβ-test is quite powerful and robust with respect to departure from normality. By combining Tiku’s robust procedure with the Fβ-test, a new robust test is developed. Some Monte Carlo studies indicate clearly that except for the uniform distribution, the -test is more powerful than the Fβ-test under non-normal distributions but has substantially the same power as the Fβtest under a normal distribution.