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.