(Demonstration Mode)

Build an advanced statistical model to evaluate the true treatment effect of your safety intervention. We look at the accident count before and after the intervention scheme was implemented, and after accounting for general trends in accident counts and regression to the mean, you can show how the effective the intervention measures really were.

Combining the expertise of leading transport software producers and academic knowledge from Newcastle University. The features demonstrated here are a prototype for a future add-in for PTV VISUM Safety

The partnership would also like to acknowledge the generous contribution from the Northumbria Safer Roads Initiative (NSRI) who have provided financial and in-kind support to the development of the software tools.

If you are a bit unsure about a part of the application, look out for our help tags.

You can *hover* over small help icons such as these:

Or you can *click or hover* on the larger help buttons like these:

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A full version will be released as an add-in to PTV Visum Safety. Sign up to our mailing list and we'll let you know when it's ready and how you can obtain a copy.

Register your interestNorthumbria.

67 reference sites in Northumbria

56 treated sites in Northumbria

years

weeks

Average
% per year

Minimum
% per year

Maximum
% per year

Trend will be modelled using a Uniform(, ) distribution.

Warning: Failure to check site exchangeability can result in inaccurate final results.

Run the test to see if the uploaded reference and treated sites are exchangeable with respect to each of the covariates included, and flag up any that aren't exchangeable.

If many warnings appear, it may be advisable to change your reference sites.

The correlation between variables in the uploaded reference dataset:

Note that this correlation matrix only shows the correlation between numeric data in your dataset. Missing values are ignored when computing the correlations.

The correlation between variables in the uploaded treated dataset:

Note that this correlation matrix only shows the correlation between numeric data in your dataset. Missing values are ignored when computing the correlations.

Prior distributions can be edited here and previewed at the bottom of the page. Vague prior distributions are used by default.

**Proceed with caution:**
Setting bad prior distributions can have a highly detrimental effect on the accuracy of your results! We recommend that you do not alter these settings unless you understand how they will affect the model.

The overdispersion parameter of the model. Larger values indicate we expect to see a greater amount of variability in inputted accident counts.

The following settings affect the accuracy and the time it will take to perform the simulation. As a rule of thumb, a longer simulation (performed with more iterations) can produce more accurate results, but it will take longer to perform the simulation. For the purposes of this demo, we have reduced the default number of iterations that are performed. This allows results to be produced quickly for the purposes of a demonstration but they may not be as accurate as a longer analysis.

No reference dataset provided!

No treated dataset provided!

Variable Selection has not been performed yet

You can download a copy of the output to reload in the results viewer. Please note that the output file can be quite large (about 1MB per site) and takes a while to compile before the download will start.

You need to perform a simulation on the dataset by clicking on the "Run simulation" button above. Once the simulation has finished, the results will automatically appear here.

A full version will be released as an add-in to PTV Visum Safety. Sign up to our mailing list and we'll let you know when it's ready and how you can obtain a copy.

Register your interest