How to fit a general-linear mixed-effects model with categorical variables?

Hi,

I am using the function fitglme from the statistics toolbox to fit a mixed-effects model with repeated measurements and categorical predictor variables as follows:

    data_nr_acquisitions=table(nr_acquisitions,problem_type,block,subject);
    glme=fitglme(data_nr_acquisitions,'nr_acquisitions ~ problem_type + block + (problem_type| subject) + (block| subject) + (1|subject)')
    anova(glme)

The variable problem_type is categorical, but the code above does not take this into account. I tried to instruct fitglme to treat problem_type as a categorical variable with the argument "CategoricalVars" but unlike fitglm the function fitglme does not accept this argument. Can fitglme handle categorical variables and how can I get it to treat a variables as categorical?

Answer 1

[Tom Lane]

Try

data_nr_acquisitions.problem_type = categorical(data_nr_acquisitions.problem_type)

before you do the fit.