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st: Fwd: [MULTILEVEL] New SIM paper by Zhang, Lu, Feng, Thurston, Xia, Zhu, and Tu


From   Stas Kolenikov <skolenik@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: Fwd: [MULTILEVEL] New SIM paper by Zhang, Lu, Feng, Thurston, Xia, Zhu, and Tu
Date   Tue, 14 Jun 2011 13:31:52 -0500

People raise other concerns with that paper, as you see below.


---------- Forwarded message ----------
From: David Judkins <JUDKIND1@westat.com>
Date: Tue, Jun 14, 2011 at 12:59 PM
Subject: [MULTILEVEL] New SIM paper by Zhang, Lu, Feng, Thurston, Xia,
Zhu, and Tu
To: MULTILEVEL@jiscmail.ac.uk


"On fitting generalize linear mixed effects models for binary
responses using different statistical packages." (pre-publication from
the Wiley website)

Not surprisingly, they got horrible results for a two-level logistic
model using GLIMMIX and some R procedures when the level 1 sample size
is just 3 per level 2 unit.  More surprising is that NLMixed still
gave decent results.

They also found startling differences between NLMIXED and glmmML run
with the Gauss-Hermite option.  Wonder if this suggests problem in
glmmML.

It would be interesting if someone were to take their examples and run
them under HLM, MLwin, and MPLUS.

One other oddity.  Most simulations have looked at the type I error
rates for null hypotheses that involve slope for some predictor =0
versus not 0.  They looked at slope=1 versus not 1.  It produces very
different results.  Any theories on why?



David Judkins
Senior Scientist
Westat
1600 Research Boulevard
Rockville, MD 20850
(301) 315-5970
DavidJudkins@westat.com


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-- 
Stas Kolenikov, also found at http://stas.kolenikov.name
Small print: I use this email account for mailing lists only.

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