Longitudinal measurement invariance PreviousNext
Mplus Discussion > Confirmatory Factor Analysis >
 Matthew Fuller posted on Wednesday, November 23, 2011 - 6:10 pm
Hi Bengt and Linda,

I'd like to conduct a test of measurement invariance for daily diary data based on mood assessments. I have roughly 30 time points (although some individuals have missing data at various time points), and 200-300 participants.

Iíve seen discussion of longitudinal measurement invariance here and elsewhere. But those examples typically focus on a much smaller number of time points. I'm wondering if the following is the most appropriate approach?

*Treat each time point as a factor, allowing the factors to correlate.
*Test configural invariance first, before evaluating the change in model fit once factor loadings etc. are constrained to be equal across time points.

My concern is that as a single level analysis, I will have a lot of factors to correlate - will the model encounter problems if my sample is 200-300 participants?

Is there another way to do this analysis (e.g., MLM with time points at level 2 and a clustering effect for individuals as well?)

Kind regards,
 Bengt O. Muthen posted on Wednesday, November 23, 2011 - 6:12 pm
How many variables do you consider per time point and how many factors?
 Matthew Fuller posted on Thursday, November 24, 2011 - 5:25 pm
Hi Bengt,

There are six items for the scale, and two factors provide a good fit for this measure.

I wasn't intending to use other variables in addition to this mood measure.
 Bengt O. Muthen posted on Friday, November 25, 2011 - 8:06 am
So you have 6 x 30 = 180 variables if you do it as a wide analysis with a longitudinal factor model. That will be heavy and won't work well with your smallish sample.

You can do it as a twolevel model, so 6 variables, 30 "cluster members", and subject as the level 2 unit, that is, using cluster=id. But then you don't get a test of measurement invariance across time as you would in a wide analysis.

So maybe you can take a wide approach and choose a few critical time points such as beginning, middle, and end in order to have fewer variables. Testing the longitudinal invariance that way.
 Matthew Fuller posted on Tuesday, November 29, 2011 - 2:02 pm
Terrific. Thank you for your help Bengt.
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