I see this question as more a matter of opinion and specific to the quantity or interest and what information you seek, however I thought some might have a pragmatic rule.

Essentially, I am writing a personal R script for generating descriptive tables to streamline my reports (like createTableOne, Stargazer etc.).

I wanted to write in a general rule for when the table should report mean (SD) or median (25th, 75th percentile) for numeric variables. Right now I have to specify for the function what I want, which is okay but I wanted to see if I could get fancier with it.

I was thinking about maybe some rule like so: if mean/median > 1.5 or <0.5 than report median (IQR).


1 Answer 1


A general rule of thumb for reporting mean or median as the defining measure of central tendency is a function of skewness. In a normally distributed distribution (with skew more or less between -1 and 1), the mean is the best measure of central tendency. With positively and negatively skewed distributions, however, median might be a better measure of central tendency. For the purposes of writing a function() (or a script, as you call it) to make your workflow more efficient, this rule of thumb might work for you. Altogether though, there is no overarching rule in this matter. Finally, I would argue for always reporting the mean over the median as it is the best measure of all participants' scores.

  • $\begingroup$ Appreciate the point, I will consider abs(skewness(x))>=1 as a rule. I do think mean is generally better, but median/mode is often done conventionally for certain variables in my field (i.e. length of hospital stay). $\endgroup$
    – KevinM
    Mar 9, 2017 at 19:35
  • 1
    $\begingroup$ @KevinM, it depends on the type of variable in question. LoS is time to event data. It cannot be normally distributed. It is typically very skewed & often rather irregular (eg, not fitting any of the 'named' survival time distributions well). It is typical (& appropriate) to use medians & quartiles for such data. This example illustrates that "there is no [nor could be any] overarching rule in this matter", as Jay states. $\endgroup$ May 21, 2018 at 19:32

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