A colleague pointed me towards the following thread https://groups.google.com/g/lavaan/c/JO5pr0fj5TY/m/AZw6722VKbwJ
for a problem I had (it was similar to the one posted in 2014 I refer to): in order to test for mediation, I had to bootstrap the SE's. I was also using 'ordered' data and, for similar reasons, was using the WLSMV estimator. Using the WLSMV estimator, however, was/is not possible when using bootstrapping.
The post offered a suggestion, but I run into the problem that roughly 1 in 10 draws the result fails to converge. Now, this is not necessarily my problem, but lavaan seems to stop the process well before the number of draws I ask to be drawn. So far i have managed to reach 291 draws.
Do I have options? I would very much like to be able to bootstrap the SE's using the WLSMV estimator. The above suggestion of adding test="scaled.shifted", seems a step in the right direction, but lavaan simply stops (I assume it is related to these unsuccessful draws?). Is there, however a way to 'force' lavaan to continue? I'd prefer to have at least 1000 successful draws.
I am using lavaan 0.6-7 and I ran the following command:
MedAppCtrlBoot2.fit <- sem(MedAppCtrl.sem,
se = "bootstrap",
test = "scaled.shifted",
bootstrap = 5000,
parallel = "multicore",
estimator = "DWLS",
summary(MedAppCtrlBoot2.fit, fit.measures=TRUE, standardized=TRUE)
PS. I have also tried the above without using parallel processing. No difference. I just hoped to speed up matters.
Thank you very much for any help.