I have used the Regression Diagnostics blog on https://stats.idre.ucla.edu/stata/we...n-diagnostics/ to check that a regression model I've built to measure the outcome of in intervention in family doctors in Scotland has had any effect. The last test in the blog relates to issue of independence (clustering/autocorrelation) and I have applied the Durbin-Watson statistic test to the dataset.
An index value (1 to 233 corresponding to the number of GP practices in the study) has was used as the time variable.
The Durbin-Watson statistic is 1.86 and the scatter plot for the residuals is attached.
The RACplot is attached.
I'm struggling to interpret the Durbin-Watson statistic coupled with the RACplot and presume that because the autocorrelations of the residuals (blue lines) are sometimes outside the MA(q) 95% CI (grey band) that there is evidence of autocorrelation.
The syntax I used was
generate index = _n
tsset index
regress Outcome i.Interven1Control0 Baseline Deprivation i.Locality
dwstat
predict r, resid
scatter r index, yline(0)
racplot
Rplot.gph
RACplot.gph
Sean MacBride-Stewart
An index value (1 to 233 corresponding to the number of GP practices in the study) has was used as the time variable.
The Durbin-Watson statistic is 1.86 and the scatter plot for the residuals is attached.
The RACplot is attached.
I'm struggling to interpret the Durbin-Watson statistic coupled with the RACplot and presume that because the autocorrelations of the residuals (blue lines) are sometimes outside the MA(q) 95% CI (grey band) that there is evidence of autocorrelation.
The syntax I used was
generate index = _n
tsset index
regress Outcome i.Interven1Control0 Baseline Deprivation i.Locality
dwstat
predict r, resid
scatter r index, yline(0)
racplot
Rplot.gph
RACplot.gph
Sean MacBride-Stewart
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