When we have more than one data point per person, typically from the same measure on more than one occasion, testing for a difference between the scores is a “paired” or “within person” test. The point is that this is different from comparing scores between different people and you can assume that a lot of things that might cause scores to be different between people (gender, age, employment, history of previous problems) are generally staying the same when scores from one person are compared. This means the statistics of how to test whether that difference appears to be systematic and not just random are different from when comparing between groups (e.g. baseline scores between first time ever help seekers and those who have had some therapy before).
The term “within subjects test” was widely used but is rightly deprecated, perpetuating the stereotype of the passive “subject” and the paradigm of the experiment rather than, more often the case in our field, survey data.
Try also … #
Effect size
Confidence interval
Cohen’s d
t-test
ANOVA (ANalysis Of VARiance)
Chapters #
Chapter 3.
Online support #
I hope to put up some simulations illustrating the distinction between paired and between person tests, and, I hope, an app allowing people to put in change data and get a full set of change analyses.
