From: Doran, Harold <HDoran_at_air.org>

Date: Sat 01 Jul 2006 - 02:57:57 EST

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Sat Jul 01 03:03:17 2006

Date: Sat 01 Jul 2006 - 02:57:57 EST

In the old version of lme, one could construct a grouped data object and
this would alleviate the need to specify the random portion of the
model. So, Spencer's call is equivalent to

fm1 <- lme(distance ~ age, random= ~age| Subject, data = Orthodont)

This condition does not hold under lmer, however.

> -----Original Message-----

*> From: r-help-bounces@stat.math.ethz.ch
**> [mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of
**> Michael Jerosch-Herold
**> Sent: Friday, June 30, 2006 12:37 PM
**> To: spencer.graves@pdf.com
**> Cc: r-help@stat.math.ethz.ch
**> Subject: Re: [R] lme convergence
**>
**> It looks like in the call to lme
**>
**> fm1 <- lme(distance ~ age, data = Orthodont,
**> + control=lmeControl(msMaxIter=1))
**>
**> you did not specify any random effects. Why not try:
**>
**> fm1 <- lme(distance ~ age, random= ~1| groupID, data = Orthodont,
**> + control=lmeControl(msMaxIter=1))
**>
**> where groupID is some factor that can be used to stratify the data.
**>
**> Also, the "Othodont" data set is used in Pinheiro & Bates
**> book, and you may want to consult that book to see the models
**> they use in connection with that data set. For the Orthodont
**> data set the groupID would most likely be the subject ID
**> ("Subject" variable).
**>
**> So a possible model would be:
**>
**> > fm1 <- lme(distance ~ age, random= ~1|Subject, data=Orthodont)
**> > summary(fm1)
**> Linear mixed-effects model fit by REML
**> Data: Orthodont
**> AIC BIC logLik
**> 455.0025 465.6563 -223.5013
**>
**> Random effects:
**> Formula: ~1 | Subject
**> (Intercept) Residual
**> StdDev: 2.114724 1.431592
**>
**> Fixed effects: distance ~ age
**> Value Std.Error DF t-value p-value
**> (Intercept) 16.761111 0.8023952 80 20.88885 0
**> age 0.660185 0.0616059 80 10.71626 0
**> Correlation:
**> (Intr)
**> age -0.845
**>
**> Standardized Within-Group Residuals:
**> Min Q1 Med Q3 Max
**> -3.66453932 -0.53507984 -0.01289591 0.48742859 3.72178465
**>
**> Number of Observations: 108
**> Number of Groups: 27
**>
**> So this runs fine.
**>
**> As, I said this data set and its analysis is discussed
**> extensively in Pinheiro and Bates book
**>
**> Michael Jerosch-Herold
**>
**>
**> >>> "Spencer Graves" <spencer.graves@pdf.com> 06/29/06 7:08 PM >>>
**> Does anyone know how to obtain the 'returnObject'
**> from an 'lme' run that fails to converge? An argument of
**> this name is described on the 'lmeControl' help page as, "a
**> logical value indicating whether the fitted object should be
**> returned when the maximum number of iterations is reached
**> without convergence of the algorithm. Default is 'FALSE'."
**>
**> Unfortunately, I've so far been unable to get it to
**> work, as witnessed by the following modification of an
**> example from the '?lme'
**> help page:
**>
**> > library(nlme)
**> > fm1 <- lme(distance ~ age, data = Orthodont,
**> + control=lmeControl(msMaxIter=1))
**> Error in lme.formula(distance ~ age, data = Orthodont,
**> control = lmeControl(msMaxIter = 1)) :
**> iteration limit reached without convergence (9) > fm1
**> Error: object "fm1" not found
**> > fm1 <- lme(distance ~ age, data = Orthodont,
**> + control=lmeControl(msMaxIter=1,
**> + returnObject=TRUE))
**> Error in lme.formula(distance ~ age, data = Orthodont,
**> control = lmeControl(msMaxIter = 1, :
**> iteration limit reached without convergence (9) > fm1
**> Error: object "fm1" not found
**>
**> I might be able to fix the problem myself, working
**> through the 'lme'
**> code line by line, e.g., using 'debug'. However, I'm not
**> ready to do that just now.
**>
**> Best Wishes,
**> Spencer Graves
**>
**> Ravi Varadhan wrote:
**> > Use "try" to capture error messages without breaking the loop.
**> > ?try
**> >
**> >
**> ----------------------------------------------------------------------
**> > ----
**> > Ravi Varadhan, Ph.D.
**> > Assistant Professor, The Center on Aging and Health Division of
**> > Geriatric Medicine and Gerontology Johns Hopkins University
**> > Ph: (410) 502-2619
**> > Fax: (410) 614-9625
**> > Email: rvaradhan@jhmi.edu
**> > Webpage:
**> > http://www.jhsph.edu/agingandhealth/People/Faculty/Varadhan.html
**> >
**> ----------------------------------------------------------------------
**> > ----
**> >
**> >> -----Original Message-----
**> >> From: r-help-bounces@stat.math.ethz.ch [mailto:r-help-
**> >> bounces@stat.math.ethz.ch] On Behalf Of Pryseley Assam
**> >> Sent: Wednesday, June 28, 2006 12:18 PM
**> >> To: R-Users
**> >> Subject: [R] lme convergence
**> >>
**> >> Dear R-Users,
**> >>
**> >> Is it possible to get the covariance matrix from an lme
**> model that
**> >> did not converge ?
**> >>
**> >> I am doing a simulation which entails fitting linear
**> mixed models,
**> >> using a "for loop".
**> >> Within each loop, i generate a new data set and analyze
**> it using a
**> >> mixed model. The loop stops When the "lme function" does not
**> >> converge for a simulated dataset. I want to inquire if there is a
**> >> method to suppress the error message from the lme
**> function, or better
**> >> still, a way of going about this issue of the loop ending
**> once the lme function does not converge.
**> >>
**> >> Thanks in advance,
**> >> Pryseley
**> >>
**> >>
**> >> ---------------------------------
**> >>
**> >>
**> >> [[alternative HTML version deleted]]
**> >>
**> >> ______________________________________________
**> >> R-help@stat.math.ethz.ch mailing list
**> >> https://stat.ethz.ch/mailman/listinfo/r-help
**> >> PLEASE do read the posting guide!
**> http://www.R-project.org/posting-
**> >> guide.html
**> >
**> > ______________________________________________
**> > R-help@stat.math.ethz.ch mailing list
**> > https://stat.ethz.ch/mailman/listinfo/r-help
**> > PLEASE do read the posting guide!
**> > http://www.R-project.org/posting-guide.html
**>
**> ______________________________________________
**> R-help@stat.math.ethz.ch mailing list
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**> PLEASE do read the posting guide!
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*

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