6 messages · Ken Beath, Luca Borger, Stuart Luppescu
Running a nested model with lme, and getting this message: Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 Can anyone explain this? Thanks.
Stuart Luppescu -=- slu .at. ccsr.uchicago.edu University of Chicago -=- CCSR ???????? -=- Kernel 2.6.28-gentoo-r5 Xander: What's going on here? People are going all Felicity with their hair.
Running a nested model with lme, and getting this message: Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 Can anyone explain this?
Usually means that some of the random effects are highly correlated or possibly zero. Ken
Thanks. -- Stuart Luppescu -=- slu .at. ccsr.uchicago.edu University of Chicago -=- CCSR ???????? -=- Kernel 2.6.28-gentoo-r5 Xander: What's going on here? People are going all Felicity with their hair.
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On 22/07/2009, at 7:54 AM, Stuart Luppescu wrote:
Running a nested model with lme, and getting this message: Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 Can anyone explain this?
Usually means that some of the random effects are highly correlated or possibly zero.
Random effects? Only the intercept is random, and in a more restricted model there's tons of variance.
Stuart Luppescu -=- slu .at. ccsr.uchicago.edu University of Chicago -=- CCSR ???????? -=- Kernel 2.6.28-gentoo-r5 Oz: Sometimes when I'm sitting in class...you know, I'm not thinking about class 'cause that would never happen... I think about kissing you. And it's like everything stops, it's like, freeze frame: Willow kissage.
On ?, 2009-07-22 at 08:15 +1000, Ken Beath wrote:
On 22/07/2009, at 7:54 AM, Stuart Luppescu wrote:
Running a nested model with lme, and getting this message: Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 Can anyone explain this?
Usually means that some of the random effects are highly correlated or possibly zero.
Random effects? Only the intercept is random, and in a more restricted model there's tons of variance.
If by a more restricted model, you mean one with less covariates, then either the covariates are reducing your random effects variance to zero or causing some other collinearity problem. Try control option for verbose output, and see if the numbers are very large. Ken
Hello,
Singularity in backsolve at level 0, block 1
in fact my experience is that in this case there is some problem with the fixed effects (e.g. not enough data for all factor combinations etc.), otherwise it would say level 1 or higher. By fitting a simpler model usually it disappears. Disclaimer: just limited empirical experience, I have never checked the code to understand better this error message, so take this with caution ;-) HTH Cheers, Luca ----- Original Message ----- From: "Stuart Luppescu" <slu at ccsr.uchicago.edu> To: "Ken Beath" <ken at kjbeath.com.au> Cc: r-sig-mixed-models at r-project.org Sent: Wednesday, July 22, 2009 12:22:56 AM GMT +01:00 Amsterdam / Berlin / Bern / Rome / Stockholm / Vienna Subject: Re: [R-sig-ME] lme error message
On 22/07/2009, at 7:54 AM, Stuart Luppescu wrote:
Running a nested model with lme, and getting this message: Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 Can anyone explain this?
Usually means that some of the random effects are highly correlated or possibly zero.
Random effects? Only the intercept is random, and in a more restricted model there's tons of variance.
Stuart Luppescu -=- slu .at. ccsr.uchicago.edu University of Chicago -=- CCSR ???????? -=- Kernel 2.6.28-gentoo-r5 Oz: Sometimes when I'm sitting in class...you know, I'm not thinking about class 'cause that would never happen... I think about kissing you. And it's like everything stops, it's like, freeze frame: Willow kissage. _______________________________________________ R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
Hello,
Singularity in backsolve at level 0, block 1
in fact my experience is that in this case there is some problem with the fixed effects (e.g. not enough data for all factor combinations etc.), otherwise it would say level 1 or higher. By fitting a simpler model usually it disappears. Disclaimer: just limited empirical experience, I have never checked the code to understand better this error message, so take this with caution ;-)
I found the problem. One of my predictors was all 0s. (Dumb me.) Thanks to everyone for the help.
Stuart Luppescu -=-=- slu <AT> ccsr <DOT> uchicago <DOT> edu
CCSR at U of C ,.;-*^*-;., ccsr.uchicago.edu
(^_^)/ ????????
[Crash programs] fail because they are based on the theory that,
with nine women pregnant, you can get a baby a month.
-- Wernher von Braun