How can one make stepAIC and lme

[Jorunn Slagstad-2]

Dear R-help

I'm working on a large dataset which I have divided into 20 subsets based on similar features. Each subset consists of observations from different locations and I wish to use the location as a random effect.
For each group I want to select regressors by a stepwise procedure and include a random effect on the intercept. I use stepAIC() and lme(). (The lmer()-function doesn't work with the stepAIC()-function.)

Since I have many groups, and I wish to do the same thing for each group, I have constructed a function which takes the dataset as input variable and gives a prediction result (here mean absolute error) as output.

This is an example using the Orthodont dataset:

library(MASS)
library(nlme)
PredRes<-function(D1)
{
lmemod=lme(distance~age*Sex, random=~1|Subject, data=subset(D1,age!=14),method="ML")
themod=stepAIC(lmemod,dir="both")
prs=predict(themod,newdata=subset(D1,age==14))
obs<-subset(D1,age==14)$distance
print(mean(obs-prs))
}

Using this function with D1=Orthodont gives:

> PredRes(Orthodont)
 Start:  AIC=345.12
 distance ~ age * Sex

 Error in subset(D1, age != 14) : object "D1" not found

The code works when I take Orthodont in directly:

> lmemod=lme(distance~age*Sex, random=~1|Subject, data=subset(Orthodont,age!=14),method="ML")
> themod=stepAIC(lmemod,dir="both")
Start:  AIC=345.12
distance ~ age * Sex

          Df    AIC
- age:Sex  1 344.49
<none>       345.12

Step:  AIC=344.49
distance ~ age + Sex

          Df    AIC
<none>       344.49
+ age:Sex  1 345.12
- Sex      1 348.70
- age      1 371.77
> prs=predict(themod,newdata=subset(Orthodont,age==14))
> obs<-subset(Orthodont,age==14)$distance
> print(mean(obs-prs))
[1] 0.2962963

How can I make this code work with dataset av input variable in a function?

I'm using R version:

Version:
 platform = x86_64-unknown-linux-gnu
 arch = x86_64
 os = linux-gnu
 system = x86_64, linux-gnu
 status =
 major = 2
 minor = 6.0
 year = 2007
 month = 10
 day = 03
 svn rev = 43063
 language = R
 version.string = R version 2.6.0 (2007-10-03)

Locale:
LC_CTYPE=en_US.UTF-8;LC_NUMERIC=C;LC_TIME=en_US.UTF-8;LC_COLLATE=en_US.UTF-8;LC_MONETARY=en_US.UTF-8;LC_MESSAGES=en_US.UTF-8;LC_PAPER=en_US.UTF-8;LC_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=en_US.UTF-8;LC_IDENTIFICATION=C

Search Path:
 .GlobalEnv, package:MASS, package:nlme, package:stats, package:graphics, package:grDevices, package:utils, package:datasets, package:methods, Autoloads, package:base

By the way the R version 2.7.0 Patched (2008-05-08 r45647) gives the same error message.

--
Regards
Jorunn Slagstad

______________________________________________
R-help@... mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

[Prof Brian Ripley]

It's a known scoping issue in lme -- you are doing this from a function.
Make sure your dataset is visible -- e.g. use with().

On Fri, 9 May 2008, Jorunn Slagstad wrote:

> Dear R-help
>
> I'm working on a large dataset which I have divided into 20 subsets based on similar features. Each subset consists of observations from different locations and I wish to use the location as a random effect.
> For each group I want to select regressors by a stepwise procedure and include a random effect on the intercept. I use stepAIC() and lme(). (The lmer()-function doesn't work with the stepAIC()-function.)
>
> Since I have many groups, and I wish to do the same thing for each group, I have constructed a function which takes the dataset as input variable and gives a prediction result (here mean absolute error) as output.
>
> This is an example using the Orthodont dataset:
>
> library(MASS)
> library(nlme)
> PredRes<-function(D1)
> {
> lmemod=lme(distance~age*Sex, random=~1|Subject, data=subset(D1,age!=14),method="ML")
> themod=stepAIC(lmemod,dir="both")
> prs=predict(themod,newdata=subset(D1,age==14))
> obs<-subset(D1,age==14)$distance
> print(mean(obs-prs))
> }
>
> Using this function with D1=Orthodont gives:
>
>> PredRes(Orthodont)
> Start:  AIC=345.12
> distance ~ age * Sex
>
> Error in subset(D1, age != 14) : object "D1" not found
>
> The code works when I take Orthodont in directly:
>
>> lmemod=lme(distance~age*Sex, random=~1|Subject, data=subset(Orthodont,age!=14),method="ML")
>> themod=stepAIC(lmemod,dir="both")
> Start:  AIC=345.12
> distance ~ age * Sex
>
>          Df    AIC
> - age:Sex  1 344.49
> <none>       345.12
>
> Step:  AIC=344.49
> distance ~ age + Sex
>
>          Df    AIC
> <none>       344.49
> + age:Sex  1 345.12
> - Sex      1 348.70
> - age      1 371.77
>> prs=predict(themod,newdata=subset(Orthodont,age==14))
>> obs<-subset(Orthodont,age==14)$distance
>> print(mean(obs-prs))
> [1] 0.2962963
>
> How can I make this code work with dataset av input variable in a function?
>
> I'm using R version:
>
> Version:
> platform = x86_64-unknown-linux-gnu
> arch = x86_64
> os = linux-gnu
> system = x86_64, linux-gnu
> status =
> major = 2
> minor = 6.0
> year = 2007
> month = 10
> day = 03
> svn rev = 43063
> language = R
> version.string = R version 2.6.0 (2007-10-03)
>
> Locale:
> LC_CTYPE=en_US.UTF-8;LC_NUMERIC=C;LC_TIME=en_US.UTF-8;LC_COLLATE=en_US.UTF-8;LC_MONETARY=en_US.UTF-8;LC_MESSAGES=en_US.UTF-8;LC_PAPER=en_US.UTF-8;LC_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=en_US.UTF-8;LC_IDENTIFICATION=C
>
> Search Path:
> .GlobalEnv, package:MASS, package:nlme, package:stats, package:graphics, package:grDevices, package:utils, package:datasets, package:methods, Autoloads, package:base
>
> By the way the R version 2.7.0 Patched (2008-05-08 r45647) gives the same error message.
>
> --
> Regards
> Jorunn Slagstad
>
> ______________________________________________
> R-help@... mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

--
Brian D. Ripley,                  ripley@...
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  [phone] (self)
1 South Parks Road,                     [phone] (PA)
Oxford OX1 3TG, UK                Fax:  [phone]

______________________________________________
R-help@... mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.