how marginal means (also called least square means) and standard deviation are calculated from repeated measure model? I do not have any "groups" in my data, I only have 76 samples each measured in 6 locations (1 location missing in one sample)

6 views (last 30 days)
I would like to calculate marginal means and std from repeated measure model or directly from raw data. I do not have any group in my data. I have 76 samples and each measured in six different location in the same sample. I would like to see effect of locations and I used repeated measure but I would like to calculate marginal mean and standard deviation of the data from the repeated measure model.

Accepted Answer

Jeff Miller
Jeff Miller on 11 May 2018
With this model I believe the marginal means and standard deviations for the different locations are simply the raw means and standard deviations of the scores at each of the locations. The model does not seem to include anything other than location that could be adjusted for (e.g., covariates).
  6 Comments
Jeff Miller
Jeff Miller on 11 May 2018
Look at the value of rm.WithinFactorNames. This is the name of the variable that you shouldo pass to multcompare. Or you could just use this:
multcompare(rm,rm.WithinFactorNames)
Mohammed Kamruzzaman
Mohammed Kamruzzaman on 11 May 2018
Thanks a million. I got exactly the same results when I used the function you mentioned. Because WithinFactorNames in rm is Time. Thanks again.

Sign in to comment.

More Answers (0)

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!