Abstract:
Homoscedasticity in the disturbance terms that appear in a regression function is one of
the key assumptions of ordinary least squares analysis. As the developed regression model
relies heavily on the model assumptions, violation of the assumptions severely affects the
importance of a regression model.
Transforming the response variable is one solution to overcome the problem of
heteroscedasticity. Today most statistical packages use graphical methods to detect
heteroscedasticity. Although a graphical method could be considered as a good starting
point, no measure of reliability can be attached to inferences derived from a graphical
method.
In this study we have developed a Minitab macro to detect heteroscedasticity present in
the disturbance terms by the use of graphical as well as statistical methods including the
popular White's General Heteroscedasticity test and how to solve the heteroscedasticity
problem by applying the alternative form of the Box-Cox power transformation.
The alternative form of the Box-Cox transformation is given by:
V=
Yln(Y) A=O
Where lnY= n-'I lnY;
Considering the stability of V for minor changes in the power parameter A, the transformed
variable, V is chosen for the analysis and useful values of A were found to be in the range
[-2, 2].
The program was developed using a Local macro structure and tested on Minitab version 14
and requires Microsoft Windows 2000 or XP operating system to implement this program.
The developed macro was tested for many data sets and was found that the program is
capable in handling the heteroscedasticity present in the error structure.
