R help - Dec 2006 - Random Effects Model

Hello,

I am new to R, and I am trying to figure out how to use it for a  
random effects model. I am using version 2.4.0, and I also have the  
book Applied Linear Regression by Sanford Weisberg.

I have four variables: Swimmer, Sex, Swim, and Difference.  Swimmer  
identifies the number assigned to a particular person. Sex is  
male/female. Swim identifies the number swim from 1 to 6. Difference  
is my variable of interest (random).

The book says I should run something like this:
> library(nlme)
> data(FREE) #FREE is my dataset
> xyplot(Difference~Swim|Type, group=Swimmer, data=FREE,
+     panel.groups=function(x,y,...){
+       panel.linejoin(x,y,horizontal=FALSE,...)}
+     )
> m1 <- lme(Difference~Swim+Type, data=FREE, random=~1+Type|Swimmer)
> m2 <- update(m1, random=~1|Swimmer)
I've pretty much decided that xyplot doesn't work. Instead, I think  
plot will work much better.  I keep getting errors about Type. Can  
someone explain this to me? Does the code above look right?

Any kind of help will be appreciated...

Thanks in advance!

Ryan

If these are the only variables, you are missing Type. Swim and Type are
both conditioning variables that you need to provide. Maybe your intention
is to use Sex instead of Type.
Try:

?xyplot

And look under x as the 1st argument for xyplot.

Rene 

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of readams at colby.edu
Sent: Monday, December 18, 2006 7:19 PM
To: r-help at stat.math.ethz.ch
Subject: [R] Random Effects Model

Hello,

I am new to R, and I am trying to figure out how to use it for a random
effects model. I am using version 2.4.0, and I also have the book Applied
Linear Regression by Sanford Weisberg.

I have four variables: Swimmer, Sex, Swim, and Difference.  Swimmer
identifies the number assigned to a particular person. Sex is male/female.
Swim identifies the number swim from 1 to 6. Difference is my variable of
interest (random).

The book says I should run something like this:
> library(nlme)
> data(FREE) #FREE is my dataset
> xyplot(Difference~Swim|Type, group=Swimmer, data=FREE,
+     panel.groups=function(x,y,...){
+       panel.linejoin(x,y,horizontal=FALSE,...)}
+     )
> m1 <- lme(Difference~Swim+Type, data=FREE, random=~1+Type|Swimmer)
> m2 <- update(m1, random=~1|Swimmer)
I've pretty much decided that xyplot doesn't work. Instead, I think plot
will work much better.  I keep getting errors about Type. Can someone
explain this to me? Does the code above look right?

Any kind of help will be appreciated...

Thanks in advance!

Ryan

______________________________________________
R-help at stat.math.ethz.ch 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.

Hi Ryan

Your model code suggests that Type is a variable that you have in your FREE data
frame, but you don't mention it, that is probably part of your problem?

The second question is how are your data structured? Sex goes in the fixed part
of the model. Swimmer is almost certainly goes in the random component, as you
have identified. The question is what to do with Swim. This could either be the
key variable of interest or simply a label representing replicates. What is the
hypothesis you're trying to test? When swimmers 1..n undertake swim 1 is
this all at the same time? If this is the case, do you have reason to believe
that there could be some similarlites (not sure what, maybe temperature, wind
conditions, fatigue) between swimmers on the same swim?

Without information on the data structure then its difficult to suggest anything
further. As a first guess you could try comparing:

m1 <- lme(Difference~Sex, random=~1|Swimmer, data=FREE)
m2 <- lme(Difference~Sex, random=~1|Swimmer/Swim, data=FREE)

With Swim in the fixed component of the model you're suggesting a linear
relationship between Difference and Swim, are you sure this is what you want? If
you really think Swim should be in the fixed compoent then you might want to
compare:

m3 <- lme(Difference~Sex*Swim, random=~1|Swimmer, data=FREE)
m4 <- lme(Difference~Sex*Swim, random=~Swim|Swimmer, data=FREE)

The latter will fit an overall relationship between Difference and Swim, and
then estimate both intercept and slope random effects for Swim.

regards

Mike D

>>> <readams at colby.edu> 19/12/2006 03:18 >>>
Hello,

I am new to R, and I am trying to figure out how to use it for a  
random effects model. I am using version 2.4.0, and I also have the  
book Applied Linear Regression by Sanford Weisberg.

I have four variables: Swimmer, Sex, Swim, and Difference.  Swimmer  
identifies the number assigned to a particular person. Sex is  
male/female. Swim identifies the number swim from 1 to 6. Difference  
is my variable of interest (random).

The book says I should run something like this:
> library(nlme)
> data(FREE) #FREE is my dataset
> xyplot(Difference~Swim|Type, group=Swimmer, data=FREE,
+     panel.groups=function(x,y,...){
+       panel.linejoin(x,y,horizontal=FALSE,...)}
+     )
> m1 <- lme(Difference~Swim+Type, data=FREE, random=~1+Type|Swimmer)
> m2 <- update(m1, random=~1|Swimmer)
I've pretty much decided that xyplot doesn't work. Instead, I think  
plot will work much better.  I keep getting errors about Type. Can  
someone explain this to me? Does the code above look right?

Any kind of help will be appreciated...

Thanks in advance!

Ryan

______________________________________________
R-help at stat.math.ethz.ch 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.


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