One way is to use Benford's Law, type -findit Benford's Law- and use
google to learn more.
Maarten
--- "Williams, Rachael" <[email protected]> wrote:
> Dear all,
>
> I am considering methods of detecting fraud in a hypothetical
> clinical
> trial with a large number of centres, but only a few patients per
> centre.
> In addition, many variables will be binary.
>
> Would Cook's D be appropriate here?
> Is it possible to calculate Mahalanobis' distance in Stata in order
> to
> detect (possibly fraudulent) inliers, outliers and near duplicates in
> a
> dataset?
>
> If anyone has any ideas of other ways to detect possible fraud I
> would
> love to hear from you too!
> Thanks - Rachael
>
>
>
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-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room N515
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
*
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