Calculating Townsend scores: Replicating published results

Amy Bonsall, one of our interns talks about how she approached the task of working out how to calculate Townsend scores and then of finding others work to compare against as a way to quality assure the methodology.

As part of the internship project to calculate deprivation scores after finding sources that provide an outline of how to calculate Townsend Deprivation Scores it was important to ensure the methodology would produce scores that matched those already published.

We wanted to calculate scores and compare them to those that had already been calculated by using the same dataset to be sure we were using the same methodology. Whilst I was focused on this, Sanah Yousaf, my partner in this internship, was creating an R script to calculate the scores. Whilst this was being developed I used Excel to calculate the scores. This was not only because we did not yet have an R script but also because I was already comfortable with Excel and it made it easy to visualise the results of each step in the calculation.

Replicating scores proved more difficult than anticipated. Not only were there limited resources of published scores but we also found that many of the people who had already calculated scores had access to unadjusted census data meaning we had different outcomes. The main problem here was, there was no way of knowing if the different data was the only reason for contrasting scores or if it could have also been down to a different formula.

I went through what felt like an endless number of attempts to replicate another’s scores. Each time I would attempt to follow the often-limited detail of the methodology. Each time I failed I’d attempt a slight variation in the calculation to see if this would work with no success. Eventually, I found a source of results calculated for 1991 by Paul Norman. Included with the results was the data used to calculate the scores as well as the Z scores for each of the indicators. The materials provided with these scores were very useful as I could ensure the scores were the same based on the exact same data. It also meant that I could check if the z scores were right before ensuring that the Townsend Deprivation Scores were correct. Success was found with this dataset and meant I could go onto calculating deprivation scores for 2011 knowing that the calculation would be correct.

The next step meant creating scores based on datasets at varied output areas, which was much easier than the previous task. After my partner in the internship, Sanah had created an R script allowing us to calculate the scores, getting results didn’t take long. From here it will be interesting to see any other obstacles that we may come across including mapping the results and comparing them to past censuses. Considering the process so far however, I look forward to confronting them face on.


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