The assumption of homoscedasticity
or homogeneity of variance is that the standard deviations of errors are approximately the same for all predicted DV scores that are presented in these Figures.
will be checked by the Levene test.
After checking the assumptions, such as outliers, normality, linearity, homoscedasticity
and independence of residuals, multiple regression was run.
There was homoscedasticity
, as assessed by visual inspection of a plot of standardized residuals versus standardized predicted values for all groups.
Thus, it can be said that the regression techniques can be applied to the series and the estimators of OLS will be consistent, always bearing in mind that the usual tests for the presence of normality and homoscedasticity
still need to be verified.
Secondly, the homoscedasticity
assumption was also violated as demonstrated by the statistical significance of Breusch-Pagan test.
Again, assumptions of normality, linearity, multicollinearity, and homoscedasticity
were evaluated, and no violations were observed.
Residual normality and homoscedasticity
were analyzed with the PROC UNIVARIATE procedure of the SAS program (SAS Institute, 2002).
The data were initially analyzed using the Shapiro-Wilk normality test and the homoscedasticity
test (Bartlett criterion).
The variance inflation factor (VIF) was calculated along with the tolerance measure to verify the multicollinearity assumption, and the Breusch-Pagan test was used to verify the residual homoscedasticity
assumption in the regression models.
This assumption is known in the literature as the homoscedasticity
of the variances.