lavaan

Hi Yves, It's a little bit strange. I ran 100 simulated datasets. Mplus, lavaan, and psych::

Yagol, I did not mean for you to search for a sequence of data sets that do not produce the error.

The default is likelihood = "normal" with sample.cov.rescale = TRUE. If for some reason you

Guido Can I ask, what is you overall objective at the end with this? Depending on that we could lead

Can you please help me with an example of the R code for doing multilevel CFA as well as the cluster

Thank you very much, Prof. Terrence! On Tuesday, 18 August 2020 at 05:04:26 UTC+8 Terrence Jorgensen

Hi, Thank you very much for the useful reference. I totally agree with Henrique, it is really great

The second model is significantly worse, based on this test. Looking at chisq and df, however, one

Yep. Looks like either your model is wrong or your sample size is insufficient (or both). On Sat, Aug

> ...I get this error message: > > Error in nlminb(start = cache$theta, objective =

It worked!! Thank you so much! :) On Monday, July 13, 2020 at 8:16:51 PM UTC+8, Patrick (Malone

On 7/13/20 12:45 AM, scorla wrote: > sample covariance matrix is not positive-definite Note that

There is an interesting paper comparing DWLS and WLSMV: DiStefano, C., & Morgan, GB (2014). A

Yes. The cfa wrapper correlates latents by default. If you haven't already, I suggest you work

It's hard difficult you can get a p-value of RMSEA > .05. The sample size influence directly

Adding that your factor correlations are very high across the board. The lowest one I spot is .76.

Attached pls find the real data `df_com`,I designed 10 factors model as below: lavaan_model<-'

what can I do when data is endogenous ordinal data and is not multivariate normal? ordered data

https://link.springer.com/article/10.1007/BF02296192 https://lavaan.ugent.be/tutorial/est.html Am

modificationindices() indicate item `q21` may affect several factors `f5`,`f6`,`f1`,`f4` as below:

Well, from a perhaps classical point of view, an exogenous variable is a variable that is not

Lets imagine I have the following data: 20 participants each rated 10 items on five different

Thank you Professor Jorgensen! I will check out the other forum, but your advice has already been

Hi Edward, Thanks a lot for all your answers. It helped me a lot! Best, Magali

":=" defines a new parameter and not the measurement model. The lavaan tutorial is very

Is it possible to constrain the loadings at level 1 across the two groups? Yes, label the parameters

On 5/29/20 11:09 PM, Terrence Jorgensen wrote: > Do you have any insight into these warnings? >

Ordinal variables should not simply be treated metrically. You can order your factors by using the

I want to conduct a 2-factor CFA with ordinal data(due to nonnormality) Nonnormality does not imply

I'm trying to run SEM (and CFA) models with categorical predictors (factor indicators) Indicators