Re: [R] lme convergence

From: Doran, Harold <HDoran_at_air.org>
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]]
> >>
> >> ______________________________________________
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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

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