I'm new to Linear Mixed Models and I'm not sure if I'm specifying the right model. I'd appreciate any feedback that confirms / disproves my model. Here's some background about my data:
I have a list of subjects. Each subject is partially crossed with an "App" group. This means that some of the "Apps" may share the same subject.
For each app, the subjects in that app answer three values on a Likert scale (
AppFrequency), and two on a continuous scale (
Security *Comfort*, and
The question I'm trying to answer is: What is the difference in
Comfort of the subjects down to?
Given this, I'm trying to model
Comfort using the following model:
comfort ~ AppImportance + AppTrust + AppFrequency + AgeOfSubject + GenderOfSubject + ComfortType + (1 | SubjectID) + (1 | App)
ComfortType is either "Security" or "Non-security".
Is my model correctly specified? Am I correct to consider
AppFrequency as fixed effects?