I have responses to a questionnaire item from a number of people, measured at equidistant timepoints. I wish to fit a growth mixture model (in R, using the LCMM package) to this data to find latent classes. My data looks something like this:
ID item-response timepoint
-----------------------
1 3 1
1 2 2
1 2 3
2 2 1
2 3 2
2 2 3
2 1 4
2 1 5
2 3 6
2 2 7
2 2 8
2 2 9
2 1 10
2 4 11
2 2 12
3 1 1
3 1 2
3 1 3
3 1 4
3 1 5
. . .
. . .
. . .
The item is one of 13 on a questionnaire on mood states. Responses are given on a Likert-scale (1 to 5).
A plot of the response curves of the first four individuals looks like this:
I am worried about the fact that the number of measurements per person is not the same. Is this a huge problem for growth mixture models or not so much?
[edit] included a column of timepoints