When we talk about "reliability" of psychometric tests, we are talking about whether it will measure the same thing consistently. While it’s a pretty simple concept in theory, it’s tougher to measure in practice.
There are quite a few different ways to test the reliability of a psychometric assessment, each offering a different ‘type’ of reliability:
This is where you get someone to take a test twice in quick succession, and see similar results both times. As you can imagine, if the results vary wildly, then the assessment isn’t hugely consistent or reliable.
This is when you compare two different psychometric assessments, each based on the same content. There are three steps to this process:
Because most tests aim to measure certain traits multiple times, it’s important that they do this consistently across different items. That’s what ‘internal consistency reliability’ measures. When we're looking for reliability in psychometric testing, there’s no point having an assessment that measures certain traits unevenly throughout!
This is where several independent judges score a particular test, and compare their results. The closer the comparison, the better the inter-rater reliability.
This can be done in two ways:
Just as it’s difficult to trust an unreliable person, you’d have a tough time relying on the results of an unreliable psychometric assessment. Think of it this way: if an assessment throws up different results every time, which result should you put your faith in? An unreliable assessment, ultimately, makes it harder for you to see true potential – not easier.
Reliability in a psychometric test is vital. But reliability doesn’t make a test valid. This can feel quite confusing, but, in short, a valid assessment measures what it says it does. So, if you think about it, you could have a test that consistently fails to measure whatever it says it will…
For a bit more on validity in psychometrics, jump to our glossary article here.
Or, if you’d like to learn a bit more about our assessment at Arctic Shores, just let us know here. We’ll get back to you pronto.
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