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question on repeated measure GLM model

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Yifei Zhang
Yifei Zhang on 5 Apr 2023
Commented: Jeff Miller on 24 Apr 2023
Dear experts,
I'm troubled about using the RM-GLM model.
Let me introduce my case. I want to use energy as the predictor variable and score as the dependent variable (each subject has only 1 score). Also, energy has two states baseline and condition, and all subjects can be divided into three groups group 1-3, using age and gender as covariates. I would like to analyse the effects within and between each group, and the interaction effects between energy, baseline vs. condition and group.
My questions are:
1) is it proper to use repeated measures ANOVA?
2) Is it appropriate to construct the model like this way,
score ~ 1 + energy * group * baseline_condition -energy:group:baseline_condition + age + gender?
3) I am confused on the regressor of contion vs. baseline, as they are two state of the energy. Can I combine the two states of energy values into one column and then add a separate column indicating that energy belongs to a condition or a baseline. In that case, the data in all other columns would have to be duplicated. Do I need to add another column for the subject ID, indicating which subject the duplicate data belongs to(then how to add the subject ID in the model)?
I'm not familiar with the fitlm function in matlab, I've used the fitglm function before. Mainly I don't understand how I should prepare the data, whether the model is correct and how to see the between and within group effects.
Any suggestions will be highly appreciated!
Best,
Yifei

Answers (1)

Jeff Miller
Jeff Miller on 6 Apr 2023
I don't fully understand the design so I won't attempt to answer questions 2) or 3), but I think this is the answer to 1):
If 'score' is the dependent variable and you only have 1 score per subject, then no, repeated measures ANOVA is not appropriate. RM ANOVAs are only applicable when there are multiple values of the DV for each subject (i.e., recorded under different conditions).
  4 Comments
Yifei Zhang
Yifei Zhang on 24 Apr 2023
Dear Jeff,
Thank you very much for your reply! I am currently switching to linear mixed effect model.
In my case, each subject had one behavioral scale score as the dependent variable, with two states of average brain energy (condition vs baseline, contineous values). Subjects were divided into 3 groups according to symptoms. Age and gender as covariates. I have tried using a two-layer model with one layer for individuals and one layer for groups. I tried these two models:
model 1) score ~ 1+age+gender+energy_base+energy_condition+energy_base:energy_condition+(1|group)+(1+energy_base|group)+(1+energy_condition|group)+(1+energy_base:energy_condition|group)
model 2) score ~ 1+age+gender+energy_base+energy_condition+energy_base:energy_condition+(1+energy_base|group+energy_condition+energy_base:energy_condition|group)
I have very little confidence in the construction of the model. I am not sure that
1) The p-values in the results are different in the random effects of the two models above when written together and separately, and I'm not sure what the difference is between the two ways of writing them.
2)I wonder if I should construct a three-layer model, with the individual as the first layer, the two energy states as the second layer, and the group as the third layer. I am not sure how the model should be constructed.
3)I would also like to include, in the model, interaction effects between groups, states, and energies.
Sorry for all the questions I've asked here, I really don't have a better source to be able to ask for advice on this question.
Best,
Yifei
Jeff Miller
Jeff Miller on 24 Apr 2023
Sorry, I don't know enough about linear mixed effects models to advise about those.

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