Hello, we are running a 3-way repeated measures anova
In our original setup for 3dLME we ran:
Where the intercepts are the random effect.
However, what if we want to include factor1 also as a random effect? What is the proper setup?
If we take out factor1 in the model in command and place it in the ranEff command, how does the model know it is still a repeated factor?
Could you offer a little bit more details? How many levels does each factor have? Any missing data? Without missing data, you can use 3dMVM.
Thanks for your response.
We are running a 4 x 3 x 3 model. All within subjects factors.
Visit: 1, 2, 3 4
Temp: 1 2 3
Trial: 1 2 3
We do have missing data for 1 subject. That subject has missing data from 1 visit. They only have data from 3 out of 4 visits.
In addition to the random effects question, there is something else:
We’ve run this model without specifying the correlation structure, so it is using compound symmetry, no? Something weird is going on with the output, that doesn’t look right compared to when we run 3dMVM with a complete data set. We aren’t expecting identical results, but not such a wide disparity… I don’t think it is something with 3dLME because I get the same results using SPSS on extracted data from a voxel. Just wondering if having data missing for an entire visit has substantial effect on the results.
How much difference is between the two results? Dramatic difference? For comparison, try 3dLME without the subject with missing data, and see if the two results have a better match.
Running 3dLME with or without the missing subject produces similar results. Both of those results differ dramatically from the 3dMVM output.
I’m not sure if it is just the nature our data set and the number of factors/levels included in the model.
Do you mind if I upload the data for you to take a look at it?
Since you have played the data at the voxel level, you may try to plot out the data at those voxels/regions where you see substantial differences, and see if that subject has significant different values from other subjects.