Critical appraisal top tips: Understanding and interpreting P values

Have you ever wanted to feel more confident about interpreting the findings of clinical trials and reviews? We’re here to help with the first in a new series of blog posts aiming to help you get to grips with understanding and interpreting biomedical research.

We’re starting this series with a post on a commonly used statistical technique – the p value. You’ve probably come across p values before as they’re often used to present results of research studies. If you’ve ever wanted to better understand what they mean then read on…

What is a P value?

A P value is a statistic that is calculated in order to show how likely it is that the result of a research study has arisen by chance alone (rather than as a result of the effect of an intervention being tested).

What do P values mean?

The key to interpreting p values is to remember that a p value of less than 0.05 is statistically significant. The threshold of 0.05 is a standard threshold used across disciplines.

A p value of less than 0.05 simply means that there is a less than 1 in 20 chance that the result of a study is due to pure random chance.

So a p value of 0.03 would be a statistically significant result, while a p value of 0.07 would not. For example, in a study such as an RCT, where measures for two groups of participants (i.e. an intervention and a control group) are being compared, a p value of less than 0.05 suggests that there is a statistically significant difference between these two groups. As the difference between the two groups passes the threshold of statistical significance, this is taken to indicate that the difference could potentially be the result of the intervention, rather than being due to chance alone.

Find out more

In the next of this regular series of posts on interpreting medical statistics we’ll look at another common statistical technique, often used alongside p values – confidence intervals. Don’t forget, we also run regular training sessions on critical appraisal for study types such as RCTs, systematic reviews and qualitative research.

In the meantime, if you want to find out more about how to interpret and understand statistics such as p values, don’t forget that a range of resources are available from the Medical Library, including:

Greenhalgh, Trisha (2014). How to read a paper : The basics of evidence-based medicine (5th ed.). Chichester: Wiley ; BMJ Books.

Kirkwood, Betty R, Kirkwood, Betty R., author, & Sterne, Jonathan A. C. (2003). Essential medical statistics (2nd ed.). Malden, Mass. ; Oxford: Blackwell Science.

Peat, J., & Barton, Belinda. (2005). Medical statistics : A guide to data analysis and critical appraisal. Malden, Mass. ; Oxford: Blackwell Pub.

Sources

Greenhalgh, Trisha (2014). How to read a paper : The basics of evidence-based medicine (5th ed.). Chichester: Wiley ; BMJ Books.