In my study there were 63 types of stimuli (63 levels of the IV) and all types had 8 different examples (8 trials per level of IV) which were all categorized by each participant. Accuracy of categorization was the dependent variable.
I originally arranged my data for R such that all 8 responses for a stimulus type were averaged into a single accuracy score by participant. Simplified example follows:
I assumed, incorrectly, that I would get the same results in a repeated measures ANOVA by arranging my data such that each stimulus example of a stimulus type constituted its own row (I am now analyzing my results with this arrangement instead of the old one). Simplified example follows:
When I ran my repeated measures ANOVA in R I got different F scores as well as different results from paired comparisons for each way I organized the data. I know that there must be a difference in how variability is calculated between the two data arrangements, but I don't understand why. Can someone give me some more insight in to why the results differ?