Are your categorical variables factors or ordered factors? If yes, lm and many other functions including, I believe, nlme, will automatically create the required dummy variables using contrasts specified by options()$contrasts. Consider the following:

> options("contrasts")
$contrasts
       unordered           ordered
"contr.treatment"      "contr.poly"

> lm(y~x, DF)

Call:
lm(formula = y ~ x, data = DF)

Coefficients:
(Intercept) xb xc 1.5 2.0 4.0


> contr.treatment(3)
 2 3
1 0 0
2 1 0
3 0 1
> options(contrasts=c(unordered="contr.helmert", ordered="contr.poly"))
> lm(y~x, DF)

Call:
lm(formula = y ~ x, data = DF)

Coefficients:
(Intercept) x1 x2 3.5 1.0 1.0


> contr.helmert(3)
 [,1] [,2]
1   -1   -1
2    1   -1
3    0    2
>

Have you studied Pinheiro and Bates (2000) Mixed-Effects Models in S and S-Plus (Springer)? I found answers to questions like yours in that book.

     hope this helps.  spencer graves

[EMAIL PROTECTED] wrote:

I'm trying to better understand the nlme package and have a few questions.



1.)

Other than using various coding strategies (e.g., dummy coding, effect coding), is 
there a way to identify group membership (i.e., treatment) directly? For example, the 
following code will fit a two group logistic growth curve (where 'Score' is repeatedly 
measured over 'Time' for each of the individuals (ID)):



nlme(Score ~ (ALPHA + Group)/(1+exp(-(GAMMA + Group)*(Time - (BETA+Group)))),

           data=LE,

           fixed=ALPHA + BETA + GAMMA ~ 1,

           random=ALPHA + BETA + GAMMA ~ 1,

           groups=~ID,

           start = c(ALPHA = 1, BETA = 3.25, GAMMA = 2.5))



Rather than specifying the effect of Group in such a manner, is there a simpler way to identify group membership in order to test the effect of group differences on the parameters of the model? I thought (removing the dummy codes and) specifying group membership by: 'groups=~ID/Groups' might work, but an error is returned. I also thought specifying group membership by :'fixed=ALPHA + BETA + GAMMA ~ 1' might work, but an error is also returned.



2.)

When will, that is under what circumstances, will there be something different than 
'~1' on the right hand side of the 'fixed' and 'random' specification lines?



3.)

Given that I figure out a way to specify group membership/treatment, how are starting 
values for both groups specified? Can the covariance structure also be given starting 
values?



Sorry for what might turn out to be simply questions. But, as of yet I've not been 
able to understand exactly what is going on. Thanks for any help you might be able to 
provide.

Have a good one,

Ken


---------------------------------


[[alternative HTML version deleted]]

______________________________________________
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html



______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html

Reply via email to