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lme - nested - One fixed effect and another within that as random effect
3 messages · Divaker, Doran, Harold, Douglas Bates
What do you mean by not working? Your lme and lmer code seem to be equivalent.
-----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 Divaker Sent: Monday, November 26, 2007 9:26 PM To: r-sig-mixed-models at r-project.org Subject: [R-sig-ME] lme - nested - One fixed effect and another within thatas random effect Dear R mixed model Users and Dr. Bates, I am trying to work out a problem given in Nested design - Design of Experiments by Montgomery - p.561 using lme It is a mixed model with Supplier as fixed effect and batches within the supplier as random effects. When I tried my hands on lmer instead of lme, I get what is required as below.
proclme=lmer(Purity~Supplier+(1|Supplier:Batch),process) print(summary(proclme))
Linear mixed-effects model fit by REML
Formula: Purity ~ Supplier + (1 | Supplier:Batch)
Data: process
AIC BIC logLik MLdeviance REMLdeviance
150.8 157.2 -71.42 146.9 142.8
Random effects:
Groups Name Variance Std.Dev.
Supplier:Batch (Intercept) 1.7162 1.3100 Here we have
the variance of random effect exactly as in the book
Residual 2.6368 1.6238
number of obs: 36, groups: Supplier:Batch, 12
Fixed effects:
Estimate Std. Error t value
(Intercept) -0.4167 0.8055 -0.5173
SupplierT2 0.7500 1.1391 0.6584
SupplierT3 1.5833 1.1391 1.3900
Correlation of Fixed Effects:
(Intr) SpplT2
SupplierT2 -0.707
SupplierT3 -0.707 0.500
But using lme, it is not working. Is there any way out.lme is
not accepting the format random=~1|Supplier : Batch I am more
comfortable using lme since the supporting docs are exaustive
and we have access to many support functions for lme
This code is not appropriate and also not working
library(nlme)
proclme=lme(Purity~Supplier,random = ~1|Supplier/Batch,process)
summary(proclme)
VarCorr(proclme)
Divaker
Dr. C. Divaker Durairaj, ME, Ph.D
Professor, Farm Machinery
Agricultural Machinery Research Centre
Tamil Nadu Agricultural University
Coimbatore 641003, India
Ph: 91-422-6611204
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On Nov 27, 2007 8:43 AM, Doran, Harold <HDoran at air.org> wrote:
What do you mean by not working? Your lme and lmer code seem to be equivalent.
Not really. Supplier:Batch is the batch grouping factor without the implicit nesting. That is, it has a different level for each different batch (which seems to me to be the only sensible way to define such a factor but, in the old days, people seemed to think it was important to specify nesting implicitly). The expression Supplier/Batch implies two random effects, one for Supplier and one for Supplier:Batch. The simple way out is to define process$realBatch <- with(process, Supplier:Batch) and fit the lme model with random = ~ 1|realBatch
-----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 Divaker Sent: Monday, November 26, 2007 9:26 PM To: r-sig-mixed-models at r-project.org Subject: [R-sig-ME] lme - nested - One fixed effect and another within thatas random effect Dear R mixed model Users and Dr. Bates, I am trying to work out a problem given in Nested design - Design of Experiments by Montgomery - p.561 using lme It is a mixed model with Supplier as fixed effect and batches within the supplier as random effects. When I tried my hands on lmer instead of lme, I get what is required as below.
proclme=lmer(Purity~Supplier+(1|Supplier:Batch),process) print(summary(proclme))
Linear mixed-effects model fit by REML
Formula: Purity ~ Supplier + (1 | Supplier:Batch)
Data: process
AIC BIC logLik MLdeviance REMLdeviance
150.8 157.2 -71.42 146.9 142.8
Random effects:
Groups Name Variance Std.Dev.
Supplier:Batch (Intercept) 1.7162 1.3100 Here we have
the variance of random effect exactly as in the book
Residual 2.6368 1.6238
number of obs: 36, groups: Supplier:Batch, 12
Fixed effects:
Estimate Std. Error t value
(Intercept) -0.4167 0.8055 -0.5173
SupplierT2 0.7500 1.1391 0.6584
SupplierT3 1.5833 1.1391 1.3900
Correlation of Fixed Effects:
(Intr) SpplT2
SupplierT2 -0.707
SupplierT3 -0.707 0.500
But using lme, it is not working. Is there any way out.lme is
not accepting the format random=~1|Supplier : Batch I am more
comfortable using lme since the supporting docs are exaustive
and we have access to many support functions for lme
This code is not appropriate and also not working
library(nlme)
proclme=lme(Purity~Supplier,random = ~1|Supplier/Batch,process)
summary(proclme)
VarCorr(proclme)
Divaker
Dr. C. Divaker Durairaj, ME, Ph.D
Professor, Farm Machinery
Agricultural Machinery Research Centre
Tamil Nadu Agricultural University
Coimbatore 641003, India
Ph: 91-422-6611204
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