lavaan 0.6-1 has been released on CRAN

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May 26, 2018, 5:58:49 AM5/26/18
to lavaan
Dear lavaan users,

Now that the windows binary has been built on CRAN, I am happy to announce that
lavaan 0.6-1 has (finally, after 15 months of work) arrived at CRAN. To install, simply to in R:

install.packages("lavaan", dependencies = TRUE)

and restart your R session.

The release notes can be found here:

The tutorial has a (short) new section on multilevel SEM:


Mark Seeto

May 27, 2018, 5:53:39 AM5/27/18
to lavaan
Thanks for all your work on lavaan, Yves. We are lucky to have such great software for free.


Carlos Lemos

May 27, 2018, 8:42:38 AM5/27/18
Dear Professor Yves Rosseel,

Thank you very much for another update of lavaan.
We cannot thank you enough for making such a great package freely available, and for maintaining this incredible help and discussion forum.

Carlos M. Lemos

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Chao Xu

May 31, 2018, 2:58:03 PM5/31/18
to lavaan
Dr. Rosseel,

Thank you very much for your hard work. We are very fortunate to have you and your team in the latent variable modeling community.

With my best regards,


Jun 2, 2018, 3:52:06 PM6/2/18
to lavaan
Dear Yves, 

Not sure if I should reply to it here, or start a new thread. 
In the previous version of Lavaan, when I used estimator = 'MLR' and computed the goodness of fit indices (GOF) for my models, the robust CFI, TLI, etc. 
However, since using the newest version of Lavaan, it shows NA values in the output. When using estimator = 'MLM', the robust GOF indices are reported as before. However, as you know, this doesn't work together with missing = 'FIML' (or 'ML'). 

Are the NA values using MLR a known issue, or am I doing something wrong?

I am happy to provide my model syntax if that helps. 

Kind regards,

Jun 8, 2018, 1:14:56 AM6/8/18
to lavaan
The best way to report an issue at github:

but I'm glad you reported this. It is a (small) bug indeed. Fixed in dev 0.6-2.1254.

As a workaround in 0.6-1, you can use

estimator = "ML", se = "robust.huber.white", test = "yuan.bentler"

instead of estimator = "MLR"

just to get these 'robust' cfi/rmsea values.

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