May I be directed to resources regarding information on the minimum sample size required for Latent Class Analysis (LCA) as well as information on conducting a power analysis for LCA? I have completed coursework in structural equation modeling and attended Dr. Muthen's training at the 2013 APS Convention however I have only recently began studying LCA and conducting analyses on MPlus therefore any information and/or insight would be greatly appreciated. Thank you very much.
Nylund, K.L., Asparouhov, T., & Muthén, B. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling. A Monte Carlo simulation study. Structural Equation Modeling, 14, 535-569.
Thank you very much Dr. Muthen. It is my understanding that LCA is not advised with sample sizes smaller than n=100. Is n=117 sufficient in some cases? Any insight as to general rules of thumb would also be greatly appreciated. I sincerely appreciate your time.
It all depends on how well the classes are separated. With binary outcomes that means how different the thresholds (conditional item probabilities) are. I have done successful mixture modeling with only 30 subjects, so I wouldn't rule out using LCA for 117 subjects. General rules of thumb are not worth much for mixtures because results depend so much on the specifics of your situation. That's why we suggest Monte Carlo studies - see the UG chapter 12. See also the Monte Carlo article:
Muthén, L.K. & Muthén, B.O. (2002). How to use a Monte Carlo study to decide on sample size and determine power. Structural Equation Modeling, 4, 599-620.
following up this trend, I also have a question about sample size in LPA. I specifically would like to know the power/suitability of my sample size (N=223) to identify different profiles based on 12 variables. I know that usually the rule of thumb is that you have 30 participants for each variable that you're including in the model, is this the case for a LPA as well? I have read the below mentioned paper but I did not find this specific information. Are there any resources about this that I can consult?
I am not familiar with that 30 rule - and I am not convinced that it is very useful since so many factors play into the power, not the least of it being how different the classes are for the means of the outcomes. There are LPA papers on our website under Papers, LCA. If you don't find power studies there, have a look at how we generated data for our UG LPA examples - each UG example has a corresponding Monte Carlo run that generates its data. You find those at