I have carried out a reaction time experiment and would now like to evaluate it. It is a repeated measures experiment with two conditions (let's call them condition A and condition B). There are also two groups (let's call them Group 1 and Group 2). Each participant has completed 60 trials in Condition 1 and 60 trials in Condition 2, so I have 120 data points for each user. I now want to do a mixed anova, and am wondering if I should use the mean of trials per participant, or if I should use each data point from each participant. I have tried in R with ezANOVA and afex to introduce each data point into the ANOVA, but then both packages give me back the warning that aggregate to the means.
This is what my Data looks like:
| ID | Group | Conditon | RT |
|---|---|---|---|
| 1 | Group 1 | A | 345 |
| 1 | Group 1 | A | 746 |
| 1 | Group 1 | A | 824 |
| 1 | Group 1 | B | 542 |
| 1 | Group 1 | B | 235 |
| 1 | Group 1 | B | 654 |
| 2 | Group 2 | A | 324 |
| 2 | Group 2 | A | 345 |
| 2 | Group 2 | A | 123 |
| 2 | Group 2 | B | 623 |
| 2 | Group 2 | B | 235 |
| 2 | Group 2 | B | 654 |
And i tried to calculate it like this:
afex::aov_car(RT ~ Group*Condition+ Error (ID/Condition), data = df_long)
i then get the warning:
More than one observation per design cell, aggregating data using `fun_aggregate = mean`.
To turn off this warning, pass fun_aggregate = mean explicitly.
