I have 10 latent variables, each consisting of 5 indicators. I am interested in the correlation between the latent variables. The sample size is only 200 so I conclude that I can not estimate the whole model at once. But would it be possible to estimate the correlation pairwise, which means I would always take 2 latent variables and estimate the correlation between them. And then continue to do this for all 45 pairs?
Thank you very much for your answer! It is usually recommended to have a sample size 5 times bigger than the number of parameters that are estimated. Is there an literature that says that a smaller sample size is enough?
In addition I have a another data set where, if I include all latent variables, the number of parameters that are estimated is bigger than the sample size. Would you then recommend a pairwise estimation of correlation between the latent variables or is this generally not a good way?