I need advice about how to carry out an ANOVA. I studied some theory of ANOVA, but apparently it is not enough.
Basically I collected around 300 reaction times for 12 subjects in my experiment. For each subject I had 2 conditions. The first has 3 levels, the second has 5 levels. Each subject went through all the possible level combinations, so I have 50 reaction times for each combination (15 different combinations), for each subject.
I want to prove the statistical significance of the different reaction time with different condition. What is not clear to me is the following point: Should I use ALL the dataset, or only the MEAN RT for each subject / condition (that is, 15 data points for each subject) ? If I use the whole dataset, I have about 10,000 data points. If I do so, the degrees of freedom for the Error is 10,557, which confuses me.
In the reaction time papers that I have around they report an F(x,y) where this x and y are usually really small, not more than 100, but their dataset is usually extremely big, more or less like mine. This make me think that they don't actually use all the reaction times, but only the mean reaction times (I suppose that, during the computation of the ANOVA, the mean of the means is then calculated).
But does this make sense, statistically?