Message-ID: <4737E17E7C8C3C4A8B5C1CE5346371D48A64A48B@EXCH06S.adqimr.ad.lan>
Date: 2016-09-01T03:45:23Z
From: David Duffy
Subject: Anova II table, df, drop1 and very complex regression models!
In-Reply-To: <000201d20386$a3571560$ea054020$@msu.edu>
Steven J. Pierce [pierces1 at msu.edu] wrote:
> I'd probably use Mplus (www.statmodel.com) for that, [...]
[snip]
> Fortunately, the lavaan package in R replicates some of what Mplus can do.
Every couple of years, I mention OpenMx on this list:
http://openmx.psyc.virginia.edu/
https://cran.r-project.org/web/packages/OpenMx/index.html
I don't know exactly how much of Mplus's functionality it provides, but suspect it would be close to 100%.
As to the OP's question, we don't know how much data is actually missing, or what pattern that takes. We also don't know why some of the fitted models differ by 0 d.f. If we did impute the data 5 times, wouldn't that give us an 80 h run-time?
Cheers, David.