I have a D-W = 1.312 with a sample of 22 cases.
Interpreting the Durbin Watson Statistic. Durbin-Watson Statistic. The errors are positively correlated. An increase in one period follows an increase in the previous period. No autocorrelation. The errors are negatively correlated. An increase in one period follows an decrease in the.
Is it a good value for running a multiple linear regression model?
2 Answers
$begingroup$If the software that you use reports the p-value, you can use it to interpret the test results. If the p-value is smaller than 0.05, you can conclude that there is no autocorrelation between your residuals.
A DW of 1.312 suggests you have some positive auto-correlation. A 'good' value is 2. Whether a value of 1.312 is a problem depends on your number of predictors. If you have 1 or 2 predictors (excluding the intercept), then your value is above the upper bound and you can't reject the null hypothesis (i.e., the DW is 'OK' at the 0.05 level of significance). If you have more than 2 predictors you may have a problem. Of course, the sample size is small so the test has low power, and there may be a benefit of bootstrapping. See here for more information.
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