question on repeated measure GLM model
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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
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回答 (1 件)
Jeff Miller
2023 年 4 月 6 日
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 件のコメント
Jeff Miller
2023 年 4 月 24 日
Sorry, I don't know enough about linear mixed effects models to advise about those.
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