I am trying to figure out the best way to design this experiment:
Each day for a month, a group of people is given a survey containing two questions: 1) What is your overall mood today? [6 point scale 0-5] and 2) Did you meet with your supervisor today? [yes or no]. I want to measure the difference in mood caused by meeting with a supervisor and provide a 95% CI.
Everyone is encouraged to participate everyday, however participation is voluntary. From a similar study, we expect around 1/3 of people to have a participation rate of 80-100%, 1/3 to have 50-80%, and 1/3 to be below 50%.
I was thinking about using a paired test, where for each participant I look at the average mood score when they met with a supervisor compared to when they didn't. One of the issues with this is there might be people that don't have both positive and negative responses to the second question. Also, there could be different numbers of responses per participant (e.g. 10 negative vs. 2 affirmative). I'm not sure how much of an issue this is and if it needs to be (or can be) controlled for.
Alternatively, I could do two sample t test where I separate Q2 affirmatives from negatives and average per person. I'm a little unsure the best way to go about this. If we think of the "no" group as the control and the "yes" group as the treatment, it seems wrong to have people show up in both groups. Should I randomly assign participants to one or the other? What if I assign someone to a group, say the affirmative, but they have no affirmative responses? And would this method be preferable to the paired scenario?