Four
main assumptions were justified before using this regression model:
linearity between dependent and independent variables; statistical independence
of the errors; homoscedasticity of the errors; and normality
of the error distribution. The stepwise regression is a semi-automated
variable selection method, where various combinations of variables
are tested at the same time (Hocking, 1976). The forward selection
method was used, where one independent variable is added at a time
allowing the increase of the R2 value. The successive addition of variables
is based solely on the t-statistics of their estimated coefficients
(Derksen and Keselman, 1992).