Why is Reliability Important?

Last week I read an interesting post on validity, and this week I am going to talk about its brother, reliability. So, why is reliability important? It’s easy when learning about scientific research and writing to feel like we’re given a whole set of rules and standards to follow and stick to, extra bits to think about and boxes to tick, when what we really want to be doing is researching psychology.

Ask Joe Bloggs on the street what he thinks about reliability, and he’ll probably say something like: “Because if your results aren’t reliable then they’ll be wrong”. And he’s right. (Do you not agree?) But are these methods helping us? Or are they a psychological form of ‘politically correct gone too far’?

Reliability and validity come together hand in hand to ensure the results of an experiment are trustworthy, realistic and correctly obtained. Validity is defined as the “extent to which a measure assesses what it is claimed to measure” (p. 261 Howitt, D & Cramer, D 2008), whereas reliability concerns consistency across different times or circumstances. An experiment could produce results which may be valid, and therefore are correctly measured, and could help us draw a conclusion, however they might not be reliable.

Reliability tells us that if one week, an experiment produces results to support hypothesis A, and that then in another experiment, either with a different sample, or a similar (if not the same) sample at a different time hypothesis A is then proven wrong, the results aren’t very reliable, and therefore there is insufficient evidence to draw a conclusion.

Reliability in psychology is often measured using statistical methods. ‘Internal reliability’ refers to how well each data value on a scale measures the concept in question. If the data is reliable, then theoretically any data value used will give the same as any other value, or indeed, all values together. Methods are used, such as ‘split half reliability’, where the first and second halves of results are separated, and then the Pearson correlation for these results is calculated. Other mathematical functions such as ‘Spearman-Brown formula’ and ‘Guttman reliability’ are also used.

More practically, tests can be repeated, either as a simple repeat (‘Test-retest reliability’) or in a different form (‘Alternate form reliability’) however this in turn can adversely affect the results, since the circumstances of participants may change, or memories of the first test can affect how participants handle the second test. Alternate forms reliability attempts to overcome the latter problem, by using a slightly different test, which resolves the issue to some extent.

Internal reliability still works hand in hand with these practical methods of ensuring reliability, e.g. after a repeat test, if we see that the value calculated for internal reliability are different from that of the original test, we can determine that results may not be reliable.

While statistics seem so lifeless, dull and uninteresting, we can see here how mathematical formulas can compensate where practical work falls short, but also vice-versa. Obviously, results must be reliable, and here we have a selection of methods that, when used in conjunction with our scientific judgement can and will help us ensure both validity and reliability of our research.

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4 comments on “Why is Reliability Important?

  1. I found your posted article to be well laid out and well structured. I thought you used good examples to explain reliability and how it is perceived by ‘non-psychology’ related public. I would agree with your ending statement about how results must be reliable for research to be classified by scientific judgement. Maybe you could bring a bit more of your personal opinion out through your post but other than that I enjoyed reading it.

  2. Enjoyable to read! I am one to always think about jus how difficult it is though to produce both validity and reliability, because for a study to be truly valid it should be very in depth and for a study to be reliable it’s more the issue of the number of studies and participants being very large so combining the two is a great difficulty. When presented with the choice, I would always go with the reliability side as this for me is a little more valuable on the scientific side of things as opposed to going for validity if I had to choose between one or the other which we often do. Nice post with a lot of personality!

  3. I agree that it’s evident that reliability is an important part of research, and I do agree with the example of Joe Bloggs. However it is my personal opinion that validity is more important that reliability.
    Just because something is reliable, does not mean it will be measuring the correct thing, where as at the same time something valid may not be able to be reproduced. However I would much rather measure, and release results of the correct nature once than i would release wrong results repeatedly. However that is just my opinion.

  4. I enjoy reading your blog which is well-written and well-structured one. Your blog give me a great insight about how important is reliability. If the results are not reliable, then the research becomes meaningless because it is not persuasive that other psychologists will not acknowledge the claims inside the research.

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