In research on people, scientists are typically interested in the group data - the mean, median, and variance of a sample of people. But according to a provocative new paper out in PNAS, the statistics of a group can obscure the variability within individuals, over time.
The paper, from Aaron J. Fisher, John D. Medaglia, and Bertus F. Jeronimus, isn't really making a new point. The pitfalls of generalizing from the group to the individual level have longbeen known - but these issues are typically discussed in the form of hypothetical scenarios or contrived examples. Fisher et al. show how these issues apply to real-world data. The authors took datasets from six psychology studies, all of which involved repeated measures from each participant: for instance, in Study #1, 43 people suffering from depression or anxiety had to rate their mood, four times each day for one month. Because each participant ...
