Sample size requirements for latent c... PreviousNext
Mplus Discussion > Latent Variable Mixture Modeling >
Message/Author
 Jason Settels posted on Tuesday, March 20, 2018 - 7:37 am
Dear MPlus users,
I have a question to ask concerning latent class analysis (LCA). I am working with a sample of 57 American cities. I am using a total of 83 city-level variables to place my 57 cities into a set of latent classes (I am considering first using exploratory factor analysis to aggregate my 83 city-level variables into 7 or so factors/indexes). My goal is to study how different latent classes of American cities are associated with the overall happiness of city residents. I am concerned that my sample size of 57 cities might be inadequate to develop a stable set of latent classes. I would very much appreciate it if anyone could offer me advice concerning whether an LCA can be done with a sample of 57. Might it be the case that I should limit the number of latent classes I develop to a certain number?
I am aware of some of the techniques (like BIC) used to establish what is the best number of latent classes to develop with LCA. I’m wondering if there is any way to get a sense of whether the outcomes of these techniques are stable and accurate.
I would very much appreciate your help, thank you in advance!
 Bengt O. Muthen posted on Tuesday, March 20, 2018 - 2:27 pm
I think N=57 is very low for mixtures unless you have say only 2 classes with very clear separation between them (for instance in terms of means for the outcomes).

You may also want to ask on SEMNET.
Back to top
Add Your Message Here
Post:
Username: Posting Information:
This is a private posting area. Only registered users and moderators may post messages here.
Password:
Options: Enable HTML code in message
Automatically activate URLs in message
Action: