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scope, lme, ns, nlme, splines

4 messages · Jacob Wegelin, Duncan Murdoch

Jacob Wegelin
# 
I want to fit a series of lme() regression models that differ only in the
degrees of freedom of a ns() spline. I want to use a wrapper function to do
this. The models will be of the form

y ~ ns(x, df=splineDF)

where splineDF is passed as an argument to a wrapper function.

This works fine if the regression function is lm(). But with lme(),
I get an error.  fitfunction() below demonstrates this.

Why?

KLUDGEfit() below provides a clumsy solution. It turns the lme()
command, along with the appropriate value of splineDF, into a text
string and then uses eval(parse(text=mystring)).  But is there not a
more elegant solution?

set.seed(5)
junk<-data.frame(x=rnorm(100))
junk$y<-junk$x + rnorm(nrow(junk))
junk$idvar<- factor(sample(LETTERS[1:10], size=nrow(junk), replace=TRUE))
library("nlme")
library(splines)

fitfunction<-function(splineDF=1) {
 	thislm<-lm( y ~ ns(x, df=splineDF), data= junk)
 	thislm
 	cat("finished thislm\n")
 	thislme<-lme(
 		fixed= y ~ ns(x, df=splineDF)
 		, random= ~ 1 | idvar
 		, data= junk)
 	thislme
}
fitfunction()

KLUDGEfit<-function(splineDF=2) {
 	thislm<-lm( y ~ ns(x, df=splineDF), data= junk)
 	thislm
 	cat("finished thislm\n")
 	mystring<-paste(
 	"thislme<-lme( fixed= y ~ ns(x, df="
 	, splineDF
 	, "), random= ~ 1 | idvar , data= junk)"
 	, sep="")
 	eval(parse(text=mystring))
 	thislme
}
KLUDGEfit()

Thanks for any insight

Jacob A. Wegelin
Assistant Professor
Department of Biostatistics
Virginia Commonwealth University
830 E. Main St., Seventh Floor
P. O. Box 980032
Richmond VA 23298-0032
U.S.A.
Duncan Murdoch
#
On 06/12/2012 2:28 PM, Jacob Wegelin wrote:
Presumably this is a bug in nlme.  Formulas have associated 
environments.  In your example, that would be the local frame of the 
fitfunction, and splineDF lives there.  It looks as though lme is not 
looking in the formula environment for the splineDF value.

Another workaround besides the one you found is to use substitute() to 
put the value of splineDF into the formula, i.e.

fitfunction<-function(splineDF=1) {
       junk$splineDF <- splineDF
      thislm<-lm( y ~ ns(x, df=splineDF), data= junk)
      thislm
      cat("finished thislm\n")
       fixed <- eval(substitute( y ~ ns(x, df=splineDF), 
list(splineDF=splineDF)))
      thislme<-lme(
          fixed= fixed
          , random= ~ 1 | idvar
          , data= junk)
      thislme
}

It's not much better than your kludge in this example, but it might be 
more convenient if you want to work with different formulas.

Duncan Murdoch
13 days later
Jacob Wegelin
# 
Your solution works beautifully for predict.lme in the same data that
were used to compute the model. But what if I want to compute the 
population fitted values in newdata? In the expanded example below,
predict.lm is able to find the object called "fixed". But predict.lme is
unable to find it and returns an error.

library("nlme")
library(splines)
library(ggplot2)
set.seed(5)
junk<-data.frame(x=rnorm(100))
junk$y<-junk$x + rnorm(nrow(junk))
junk$idvar<- factor(sample(LETTERS[1:10], size=nrow(junk), replace=TRUE))
PRETTYNEWDATA<-data.frame(x=seq(-2, 2, length=20))

fitfunction<-function(splineDF=1) {
       fixed <- eval(
          substitute(
                expr= y ~ ns(x, df=splineDF)
                , env= list(splineDF=splineDF)
             )
          )
 		thislm<- lm( fixed , data= junk)
 		junk$fitlm<-predict(thislm)
       thislme<-lme( fixed= fixed , random= ~ 1 | idvar , data= junk)
       junk$fitlme<-predict(thislme,level=0)
       print(
          ggplot( junk, aes(x, y))
             + geom_point(shape=1)
             + geom_line( aes(x, fitlme), color="red", lwd=2)
             + geom_line( aes(x, fitlm), color="blue", lty=3)
 				+ ggtitle(deparse(fixed))
          )
       PRETTYNEWDATA$fitlm<-predict(thislm,newdata=PRETTYNEWDATA)
 		print(head(PRETTYNEWDATA))
 	cat("about to use newdata with lme \n")
       PRETTYNEWDATA$fitlme<-predict(thislme,level=0, newdata=PRETTYNEWDATA)
       thislme
}

Jake Wegelin
On Thu, 6 Dec 2012, Duncan Murdoch wrote:

            

      
      
      
    

        

      
      
    

            

      
      
      
    

  
  


  


      

    

    

      
      

        


  

        

      Duncan Murdoch
    

    

      
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On 12-12-19 5:02 PM, Jacob Wegelin wrote:

            

      
      
      
    

        
I didn't offer a solution, I offered a workaround for a bug.  The 
solution is to fix the bug.  I don't know how to do that.

Duncan Murdoch

In the expanded example below,