Counterbalanced caffine within subject repeated experiment

#1
Dear all,

I was wondering if anyone could give me some pointers about how to analyze my thesis experiment.
We had 12 participants, each performed something called "Random dot motion" cognitive tests with coffee
and decaffinated coffee (randomly counterbalanced) on two separate days.
This test gives response times and correct wrong data. (Each block of trials were about 200 choice tasks)
There was also a speed-accuracy trade off condition. One where they had to answer quickly within 1 second
(forced deadline speed) and another one where accuracy was the point and there was no deadline. (I am also struggling with how our experiment actually could show that caffine has an effect on the speed-accuracy trade off but I think I have some ideas about that...)

Now I am wondering which analysis to perform.
In similar studies some have done paired t-tests, and other studies seem to be doing repeated measures ANOVA, and looking at interactions.
The main problem is that there was a lot of learning, so the differences from one day to the other is mainly learning.
From what I can understand it seems I have two options, one is the repeated measures ANOVA,
and seeing if there is an interaction effect treatment*time, the other is to group all caffine
and all non-caffine trials together and doing one way paired t-test? Since the counterbalancing was done randomly is this possible?

Also not sure which assumtions I need to check for the tests to be valid, in the ANOVA I guess it is normality of the residuals and sphericity.

Sorry if this is a stupid question, any help would be greatly appreciated.
If any more information is needed please ask and I will try to elaborate further.
 

Karabiner

TS Contributor
#2
The main problem is that there was a lot of learning, so the differences from one day to the other is mainly learning.
But you said that conditions were counterbalanced.
From what I can understand it seems I have two options, one is the repeated measures ANOVA,
and seeing if there is an interaction effect treatment*time, the other is to group all caffine.
I may be wrong, but "time" would represent the order of treatments, i.e. a between-subjects factor. Two repeated-measures factors do not make sense here, AFAICS.

With kind regards

Karabiner
 
#3
Thank you for the reply Karabiner:)

Yes, it was counterbalanced. Isn't the between subject factor what differed between the groups? So, one group was given caffeine on the first testing and the other on the other day. All other things were the same for all participants.

I am mainly wondering about how to deal with a counterbalanced experiment. Do I look at interactions with caffeine on time with ANOVA? From what I understood with talking with some professors at my university this is one way to do it. Looking at it visually this would look like two lines going from day one to day two, with two lines, one for caffeine first day and the other for the other day. If caffeine had no effect the lines would be parallel, while if they crossed and the interaction was significant this would mean that there was an effect from caffeine.

I was wondering if it is possible to do a one way paired t-test? To put all caffeine trials and and all non-caffeine trails together and check if the difference was significant? I am not sure if this is possible. I am just wondering since it seems this is what it seems the have done in a comparable experiment about alcohol :https://link.springer.com/article/10.1007/s00213-011-2435-9.