Construct Validity
Construct valdity relates to whether a particular psychometric assessment...
Lead consultant at Test Partnership, Ben Schwencke, explains how norm groups work in psychometric assessments.
Norm Groups in Psychometric Assessments. Now, when using psychometric assessments you'll almost always be asked to choose one particular norm group from a list.
Now, what are norm groups and why do we use them?
And the simple answer is a norm group is a collection of scores, from a relevant population, which allows you to benchmark i.e. if you're looking at graduates.
A graduates' norm group will allow you to compare your candidates scores to that of graduates as a whole, so you'll know how well they do relative to the chosen population.
Now when designing psychometric assessments collecting norm group data is an essential part of the process because it is so valuable to the selection process as a whole.
What happens is typically a psychometric test publisher will go to, say, universities, in the case of developing graduate norm groups, and recruit participants to help in developing the assessment.
You'll get hundreds, possibly thousands, maybe tens of thousands of graduates to sit and to complete the assessment before you brought it to market, in order to find out what the average score is and the distribution of those scores.
You would do this for as many populations as you would like to test for, so it could be graduates, it could be apprentices, it could be professionals managers, executives, it could even be specific roles i.e. finance, accountancy, legal professionals, it's all intrinsically important to benchmarking and to ensuring that the scores you generate are contextually relevant.
Now, once you have your norm group data, and it is always a process getting their data, analysing it is feasible.
When you have, say, a thousand graduates and their scores first thing you do is you find out the average score - usually just using the mean.
And then you would look at the distribution of those scores, typically the standard deviation.
Once you have that information you'll know how well the average graduate does, say if it's a fifteen question assessment, 10 out of 15 perhaps, and the standard deviation i.e. plus or minus 2, 3, something like that.
These are scores which are automatically contextualised for that particular population.
Once you have that information you can create what we call norm-referenced scores.
So if you have a graduate, they complete the assessment and they score at the 50th percentile, what that means is they're exactly average for that population.
If they scored the 80th percentile it means they are in the top 20% their population and if they score the 20th percentile it means they're at the bottom 20%.
Now the fact is, one of the reasons we call them a norm group is that it follows the normal distributions, sort of bell curve, with most people scoring in the middle in the average range, and comparatively fewer people scoring at the extremes.
Hence, norm group.