[R-sig-ME] lme and lmer

S Ellison S.Ellison at LGCGroup.com
Wed Jul 30 14:43:56 CEST 2014 


> Thank you, that explains everything!
... except the model?

This is an aside to the OP's question, but ?coop says - with some reason given that run to run effects tend to be random inside analytical chemistry labs - that batch is _nested_ in Spc/Lab.

random =~1|Bat doesn't do that; it leaves batch crossed with Lab. You'd surely have to create a Lab:Bat interaction factor and put that in the random part to achieve a nested model.

Steve Ellison

> 
> Nick
> 
> -----Original Message-----
> From: Viechtbauer Wolfgang (STAT)
> [mailto:wolfgang.viechtbauer at maastrichtuniversity.nl]
> Sent: 30 July 2014 09:47
> To: Nicholas Burgoyne; r-sig-mixed-models at r-project.org
> Subject: RE: lme and lmer
> 
> If you want to fit the same models, you should use:
> 
> lme <- lme(fixed=Conc ~ Lab, data=coop, random = ~ 1 | Bat,
> subset=coop$Spc=="S1")
> 
> I am surprised that it even ran with 'random = ~ Bat' (lme in R throws an
> error).
> 
> Best,
> Wolfgang
> 
> --
> Wolfgang Viechtbauer, Ph.D., Statistician
> Department of Psychiatry and Psychology
> School for Mental Health and Neuroscience
> Faculty of Health, Medicine, and Life Sciences
> Maastricht University, P.O. Box 616 (VIJV1)
> 6200 MD Maastricht, The Netherlands
> +31 (43) 388-4170 |
> http://webdefence.global.blackspider.com/urlwrap/?q=AXicE2Rm4DNkYIjxY
> GAoyqk0MknUKy4q08tNzMxJzs8rKcrP0UvOz2UoNgu1NPI2MTQwsDQ2NGU
> o1kvNyckszs9zyElPTi_KLy0Aq8ooKSmw0tcvLy_XKy9LSixNLQILQwAATP4fJA&
> Z
> 
> > -----Original Message-----
> > From: r-sig-mixed-models-bounces at r-project.org [mailto:r-sig-mixed-
> > models-bounces at r-project.org] On Behalf Of Nicholas Burgoyne
> > Sent: Wednesday, July 30, 2014 10:26
> > To: r-sig-mixed-models at r-project.org
> > Subject: [R-sig-ME] lme and lmer
> >
> > Dear all,
> >
> > I have been kindly redirected here by Ben Bolker, thank you for your
> > assistance so far!
> >
> > I apologise for posting what is probably quite a benign query, but for
> > the life of me I can't find an answer.
> >
> > I have been asked to explain the differences in the
> > variance-covariance data in an identical test in Splus (lme) and R (lmer in
> lme4).
> >
> > The input data is standard (from MASS), and identical (I've checked),
> > the test is as similar as I can make it (code below).
> >
> > The same output (to a high degree of precision) is obtained for all of
> > the output values (not just that displaced here), expect for the vcov
> > data for the Intercept with itself. The effect is therefore that the
> > standard deviations of the fixed values are quite different!
> >
> > I am using splus 6.2, R 3.0.2 and lme4 v 1.1-7 (see sessionInfo dump
> > later on), the contrasts in splus are set to treatment/poly.
> >
> > Any advice you could give me would be very helpful.
> >
> > Kind regards,
> >
> > Nick Burgoyne
> >
> > #########
> > #In Spus#
> > #########
> > >options(contrasts=c("contr.treatment", "contr.poly"))
> > >library(MASS)
> > >coop <- coop
> > >lme <- lme(fixed=Conc ~ Lab, data=coop, random = ~ Bat,
> > subset=coop$Spc=="S1")
> > > lme
> > Linear mixed-effects model fit by REML
> >   Data: coop
> >   Subset: coop$Spc == "S1"
> >   Log-restricted-likelihood: 20.27187
> >   Fixed: Conc ~ Lab
> >  (Intercept)      LabL2 LabL3 LabL4     LabL5     LabL6
> >     0.319999 0.08166667  0.04  0.68 0.1233333 0.2033333
> >
> > Random effects:
> > Formula:  ~ Bat | 1
> > Structure: General positive-definite
> >                   StdDev   Corr
> > (Intercept) 0.1401167895 (Intr) BatB2
> >       BatB2 0.0001407246  0.000
> >       BatB3 0.0003628541  0.000 -0.072
> >    Residual 0.1029156551
> >
> > Number of Observations: 36
> > Number of Groups: 1
> > > lme$varFix
> >              (Intercept)        LabL2        LabL3        LabL4
> > LabL5        LabL6
> > (Intercept)  0.021398003 -0.001765272 -0.001765272 -0.001765272 -
> > 0.001765272 -0.001765272
> >       LabL2 -0.001765272  0.003530544  0.001765272  0.001765272
> > 0.001765272  0.001765272
> >       LabL3 -0.001765272  0.001765272  0.003530544  0.001765272
> > 0.001765272  0.001765272
> >       LabL4 -0.001765272  0.001765272  0.001765272  0.003530544
> > 0.001765272  0.001765272
> >      LabL5 -0.001765272  0.001765272  0.001765272  0.001765272
> > 0.003530544  0.001765272
> >       LabL6 -0.001765272  0.001765272  0.001765272  0.001765272
> > 0.001765272  0.003530544
> >
> > ######
> > #In R#
> > ######
> > >library(lme4)
> > >library(MASS)
> > >coop <- coop
> > >lme <- lmer(formula=Conc ~ Lab + (1|Bat),  data=coop,
> > subset=coop$Spc=="S1")
> > >lme
> > Linear mixed model fit by REML ['lmerMod']
> > Formula: Conc ~ Lab + (1 | Bat)
> >    Data: coop
> > Subset: coop$Spc == "S1"
> > REML criterion at convergence: -40.5438 Random effects:
> > Groups   Name        Std.Dev.
> > Bat      (Intercept) 0.0000
> >  Residual             0.1029
> > Number of obs: 36, groups:  Bat, 3
> > Fixed Effects:
> > (Intercept)        LabL2        LabL3        LabL4        LabL5
> > LabL6
> >     0.32000      0.08167      0.04000      0.68000      0.12333
> > 0.20333
> > >vcov(lme)
> > 6 x 6 Matrix of class "dpoMatrix"
> >              (Intercept)        LabL2        LabL3        LabL4
> > LabL5
> > (Intercept)  0.001765278 -0.001765278 -0.001765278 -0.001765278 -
> > 0.001765278
> > LabL2       -0.001765278  0.003530556  0.001765278  0.001765278
> > 0.001765278
> > LabL3       -0.001765278  0.001765278  0.003530556  0.001765278
> > 0.001765278
> > LabL4       -0.001765278  0.001765278  0.001765278  0.003530556
> > 0.001765278
> > LabL5       -0.001765278  0.001765278  0.001765278  0.001765278
> > 0.003530556
> > LabL6       -0.001765278  0.001765278  0.001765278  0.001765278
> > 0.001765278
> >                    LabL6
> > (Intercept) -0.001765278
> > LabL2        0.001765278
> > LabL3        0.001765278
> > LabL4        0.001765278
> > LabL5        0.001765278
> > LabL6        0.003530556
> >
> > > sessionInfo()
> > R version 3.0.2 (2013-09-25)
> > Platform: i386-w64-mingw32/i386 (32-bit)
> >
> > locale:
> > [1] LC_COLLATE=English_United Kingdom.1252 [2]
> LC_CTYPE=English_United
> > Kingdom.1252 [3] LC_MONETARY=English_United Kingdom.1252 [4]
> > LC_NUMERIC=C [5] LC_TIME=English_United Kingdom.1252
> >
> > attached base packages:
> > [1] stats     graphics  grDevices utils     datasets  methods   base
> >
> > other attached packages:
> > [1] MASS_7.3-29  lme4_1.1-7   Rcpp_0.11.2  Matrix_1.1-4
> >
> > loaded via a namespace (and not attached):
> > [1] grid_3.0.2      lattice_0.20-29 minqa_1.2.3     nlme_3.1-111
> > [5] nloptr_1.0.0    splines_3.0.2   tools_3.0.2
> >
> > --
> > Nicholas Burgoyne
> > E:nburgoyne at mango-solutions.com	T:+44 (0)1249 705 450
> > W:www.mango-solutions.com
> 
> --
> 
> LEGAL NOTICE\ \ This message is intended for the use of ...{{dropped:18}}
> 
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models


*******************************************************************
This email and any attachments are confidential. Any use...{{dropped:8}}

More information about the R-sig-mixed-models mailing list