[R-sig-ME] valid estimates using lme4?

[Alessandro Moscatelli]

The authors states:

"Judging from the results of our simulation study, we conclude that
the SAS NLMIXED procedure
provides the most accurate parameter estimates and inference (type I
error) under correct model
assumptions. Among the remaining procedures, estimates are generally
biased, especially the type I
errors, with the level of accuracy depending not so much on the number
of quadrature points (for
the procedures based on the integral approximation), but rather on the
magnitude of the values of the
parameters."

This is not my personal opinion (I don't use SAS at all...I am an
R-addicted!) I am just citing the article...

2011/10/29 Abhijit Dasgupta <adasgupta at araastat.com>:
> Going over the paper quickly, it is just as much an indictment of SAS as it
> is of R. So much for "validated statistical package".
>
> On Sat, Oct 29, 2011 at 6:42 AM, Alessandro Moscatelli <moskante at gmail.com>
> wrote:
>>
>> The referee may have this article in mind:
>>
>>  Zhang H, Lu N, Feng C, Thurston SW, Xia Y, Zhu L, Tu XM. On fitting
>> generalized linear mixed-effects models for binary responses using
>> different
>> statistical packages. Stat Med. 2011 Jun 10. doi: 10.1002/sim.4265. [Epub
>> ahead
>> of print] PubMed PMID: 21671252; PubMed Central PMCID: PMC3175267.
>>
>> when he ask for a "validated statistical package (SAS, STATA, SPSS) as
>> lme4 is known not to be the best". Hope this can help you with the
>> answer!
>>
>> Alessandro Moscatelli
>> Department of Cognitive Neuroscience
>> Bielefeld Univerisy (DE)
>>
>> _______________________________________________
>> R-sig-mixed-models at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
>