[R] Estimators for non-normal data

[Nika Sušac]

Yes, I meant confirmatory factor analysis, I'm sorry if I wasn't clear. I
was doing my analyses in lavaan and saw that there are several robust
options (MLM, MLMVS, MLMV, MLF, MLR), but I wasn't sure about their
specifics, so that was what I was actually asking about.
I will definitely consult the links you sent me, thank you!

2016-07-25 11:46 GMT+02:00 Martin Maechler <maechler at stat.math.ethz.ch>:

> >>>>> Nika Sušac <nika.susac at gmail.com>
> >>>>>     on Sat, 23 Jul 2016 19:39:48 +0200 writes:
>
>     > Hi!  I have non-normal data (items are continuous on a
>     > 9-point scale, but not normally distributed) and I want to
>     > conduct cfa. Which of the estimators available in lavaan
>     > do you recommend me to use?  Thanks in advance!
>
> I think you want *robust* statistical methods then.
>
> Robust factor analysis (if 'cfa' means something like that) is
> somewhat prominent topic.
> Simple approaches will already be available by using
> MASS::cov.rob() for a robust covariance matrix which you then
> can pass to other methods.
>
> For more (and more modern) methods and approaches,
>
> - for R packages, I'd recommend you consult the CRAN task view
>   about robust statistical methods,
>         https://cran.r-project.org/web/views/Robust.html
>   notably the section on 'Multivariate Analysis'
>
> - for more specific help and expertise, I strongly recommend
>   the dedicated  R-SIG-robust mailing list (instead of R-help),
>    --> https://stat.ethz.ch/mailman/listinfo/r-sig-robust
>
> Best regards,
> Martin Maechler, ETH Zurich
>
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>

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