Wednesday, 13 April 2011

A short nerdy post about use of percentiles in statistical analyses




  1. Thanks for this - as always you explain things very clearly! I'll be keeping a bookmark to send it to offending articles I'm reviewing, or confused project students.

  2. Overall one has to question the validity of statistics in the sense that they can only give a broad insight into the data. fMRI is a good example of how statistical analysis actually distances you from reality whilst giving the impression it does the opposite. The resolution statistical analysis gives is just not high enough for such endeavors but you have no real way of knowing. Silly headlines from fMRI studies attest to that.

  3. Just a quick comment about statistical procedures that assume normality, namely ANOVA - according to Monte Carlo tests (Johnson, 1993), ANOVA (and even ANCOVA) are robust to violations of most assumptions including extremely skewed distributions and/or heterogeneity of group variances, assuming a balanced design and adequate group sizes (N>30).

    Johnson, C. C. (1993). The Effects of Violation of Data Set Assumptions when Using the Oneway, Fixed Effects Analysis of Variance and the One Concomitant Analysis of Covariance Statistical Procedures. Paper presented at the Annual Meeting of the Mid-South Educational Research Association (New Orleans, LA, November 10-12, 1993). Retrieved from: on 27/4/2011

  4. Thanks for the comment Ben. I agree it makes sense not to worry too much about normality if you start out with a non-normal dataset, provided it isn't too severely non-normal. But what makes no sense is to take a normally distributed dataset and do stats on the percentile scores, as you are in effect deliberately modifying it to make it non-normal. And as the stats on the example above illustrate, that reduces power to detect genuine effects.


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  6. Results from psychological tests can be expressed in various ways. Percentiles are a popular format in clinical reports, because they can be explained to . feng shui