I am confronted with the following problem:
To evaluate a questionnaire's factor structure via confirmatory factor Analysis we collected data of 140 participants.
37 of them have either one or two items missing.
The data is ordinal so i concluded that I have to use the WLSMV estimator in lavaan.
When I did so few weeks ago using an older version of lavaan I was able to use ' missing = "ml"' ' and R gave me a nice output telling me that it used all 140 participants via the DWLS estimator.
I was rather happy to have "solved" the problem of missings until I read deeper into the topic and found out that there must be a mistake because WLSMV wouldn't use missings and as far as I understand it was a kind of "bug" in the old Version of lavaan that made it possible to specify the "ml" - estimator for missing - whatever then happend behind the scenes.
Meanwhile my colleagues wrote a nice paper that included my findings so what I am looking for is as follows:
What exactly did I compute via my analysis and is there any chance that it can be of use once I understand what really happened?
Would multiple imputation for the missings be a good way to go to be able to use all 140 participants? The whole paper is now based on that number (it investigates other topics aswell) so I would be really glad to find a way to keep that.
Thank you all for taking the time