Did the numer of accidents or casualaties for the months in 2005-2007
influence the decision to make the intervention at this site?
If so, you need to allow for regression to the mean if you can, or
recognise that your result is subject to it if you cannot. If not, you
do not need to allow for regression to the mean.
If the result is subject to regression to the mean, then to allow for it
using the empirical Bayes method, you need an estimate of the
distribution of accident or casualty numbers in the before period at
sites sufficiently similar to yours to have been candidates for the sam
intervention if they had had enough accidents or casualties in the
before period.
If you do not have such an estimated distribution, you cannot estimate
the effect of regression to the mean. This is not always recognised by
those who advocate applying the empirical Bayes method.
Richard Allsop
Dr John C Bullas wrote:
> As an earth scientist and road surface specialist I am outisdeof my
> comfort zone with accident statistics
>
> I have data for values for KSIs and slights for the months September
> to December for 2008 when an
> intervention was in place and for the same months for 2005-2007 when it was not
>
> I believe since I cannot show the data is normally distributed, the
> wilcoxon rank sum test might be
> the best measure of whether 2008 is significantly lower than the other
> years (as a group)
>
> I do not have control data to hand nor traffic flows so will have to
> state an assumption
>
> Is this test (aka MANN -WHITNEY 'U' ?) a good choice?
>
> Dr B
--
Richard Allsop
Centre for Transport Studies
University College London
Gower Street
London
WC1E 6BT
email [log in to unmask]
www.cts.ucl.ac.uk
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