Section author: Danielle J. Navarro and David R. Foxcroft

An illustrative data set

Suppose you’ve become involved in a clinical trial in which you are testing a new antidepressant drug called Joyzepam. In order to construct a fair test of the drug’s effectiveness, the study involves three separate drugs to be administered. One is a placebo, and the other is an existing antidepressant / anti-anxiety drug called Anxifree. A collection of 18 participants with moderate to severe depression are recruited for your initial testing. Because the drugs are sometimes administered in conjunction with psychological therapy, your study includes 9 people undergoing cognitive behavioural therapy (CBT) and 9 who are not. Participants are randomly assigned (doubly blinded, of course) a treatment, such that there are 3 CBT people and 3 no-therapy people assigned to each of the 3 drugs. A psychologist assesses the mood of each person after a 3 month run with each drug, and the overall improvement in each person’s mood is assessed on a scale ranging from -5 to +5. With that as the study design, let’s now load clinicaltrial data set. It contains the three variables drug , therapy and mood.gain .

For the purposes of this chapter, what we’re really interested in is the effect of drug on mood.gain. The first thing to do is calculate some descriptive statistics and draw some graphs. In Descriptive statistics we showed you how to do this, and some of the descriptive statistics we can calculate in jamovi are shown in Fig. 130.

Fig. 130 Descriptives for mood.gain, and box plots by drug administered

As the plot makes clear, there is a larger improvement in mood for participants in the Joyzepam group than for either the Anxifree group or the Placebo group. The Anxifree group shows a larger mood gain than the Placebo group, but the difference isn’t as large. The question that we want to answer is are these difference “real”, or are they just due to chance?