fyi, this may (or may not) be of interest to folks here, but a new paper is out comparing software (SAS and R, including lme4 and glmmML) for fitting GLMMs via simulation. getting some chatter over on the multilevel listserv. cheers, dave Dave Atkins, PhD Research Associate Professor Department of Psychiatry and Behavioral Science University of Washington datkins at u.washington.edu Center for the Study of Health and Risk Behaviors (CSHRB) 1100 NE 45th Street, Suite 300 Seattle, WA 98105 206-616-3879 http://depts.washington.edu/cshrb/ (Mon-Wed) Center for Healthcare Improvement, for Addictions, Mental Illness, Medically Vulnerable Populations (CHAMMP) 325 9th Avenue, 2HH-15 Box 359911 Seattle, WA 98104 http://www.chammp.org (Thurs) -------- Original Message -------- Subject: Re: New SIM paper by Zhang, Lu, Feng, Thurston, Xia, Zhu, and Tu Date: Tue, 14 Jun 2011 14:15:24 -0500 From: Brian R Gray <brgray at USGS.GOV> Reply-To: Multilevel modelling discussion list <MULTILEVEL at JISCMAIL.AC.UK> To: MULTILEVEL at JISCMAIL.AC.UK possible that these results reflect R coding from 2009 (when the paper was submitted). as weak evidence, note that the authors define GLIMMIX as being constrained to PQL only (GLIMMIX has offered Gaussian quadrature and Laplacian estimation for some time) Brian From: David Judkins <JUDKIND1 at WESTAT.COM> To: MULTILEVEL at JISCMAIL.AC.UK Date: 06/14/2011 01:00 PM Subject: [MULTILEVEL] New SIM paper by Zhang, Lu, Feng, Thurston, Xia, Zhu, and Tu Sent by: Multilevel modelling discussion list <MULTILEVEL at 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 at westat.com -------------------------- Multilevel list -------------------------- To leave, send leave multilevel to jiscmail at jiscmail.ac.uk For further info about the Multilevel list, please see http://www.jiscmail.ac.uk/lists/multilevel.html and http://www.nursing.teaching.man.ac.uk/staff/mcampbell/multilevel.html -------------------------- Multilevel list -------------------------- To leave, send leave multilevel to jiscmail at jiscmail.ac.uk For further info about the Multilevel list, please see http://www.jiscmail.ac.uk/lists/multilevel.html and http://www.nursing.teaching.man.ac.uk/staff/mcampbell/multilevel.html
New SIM paper by Zhang, Lu, Feng, Thurston, Xia, Zhu, and Tu
1 message · David Atkins