Modified Levene Test

Without even doing a statistical test, it is obvious that, as months go by, the variability in the data increases. Nevertheless, let us perform the Modified Levene Test. 

Heteroskedasticity can be evaluated by means of several statistical tests (modified Levene, White, or Breusch-Pagan test) or by looking at the residual plots [20-22],... 

We will consider Xi (months) as the main predictor value with the greatest value range, 1 through 12. Note, by a t-test, each independent predictor variable is highly significant in the model (p < 0.01). A plot of the e,s vs. xi, presented in Figure 8.11, demonstrates, by itself, a nonconstant variance. Often, this pattern is masked by extraneous outlier values. The data should be cleaned of these values to better see a nonconstant variance situation, but often the Modified Levene will identify a nonconstant variance, even in the presence of the noise of outlier values. 

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