R help - Apr 2012 - Degrees of Freedom for lme.

Hi, 

I am trying to run a linear mixed effect model on data.  I have 17
longitudinal subjects and 36 single subjects, and this is the code I'm using
(below).  So, INDEX1 is the column with brain volumns, and the predictors
are gort and age, by time ID (time they were seen).  

I believe my data is set up the right way, but when I run it, I get DF for
Intercept is 49, and DF for slope is 13?  Why?   

lme.gort=lme(Volume ~ GORT_FLUENCY+AGE, random = ~ 1 | TIMEID, data
subset(vol_data, INDEX1=='LH_FUSIFORM'), na.action=na.omit)
 
 
 fit_vol_model1 <- function(df){
     tryCatch(lme.gort <- lme(Volume ~ GORT_FLUENCY+AGE, random = ~ 1 | UID,
data=df, na.action=na.omit), error=function(err) tag <<-1)
     data.frame(Term = rownames(anova(lme.gort)), anova(lme.gort))
+  }
  models = list()
  models$anova = ddply(vol_data, c("INDEX1"), fit_vol_model1)
  summary(lme.gort)

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SHouston <suzannehouston <at> gmail.com> writes:
> I am trying to run a linear mixed effect model on data.  I have 17
> longitudinal subjects and 36 single subjects, and this is the code I'm
using
> (below).  So, INDEX1 is the column with brain volumns, and the predictors
> are gort and age, by time ID (time they were seen).  
> 
> I believe my data is set up the right way, but when I run it, I get DF for
> Intercept is 49, and DF for slope is 13?  Why?   
> 
> lme.gort=lme(Volume ~ GORT_FLUENCY+AGE, random = ~ 1 | TIMEID, data >
subset(vol_data, INDEX1=='LH_FUSIFORM'), na.action=na.omit)
> 
>  
>  fit_vol_model1 <- function(df){
>      tryCatch(lme.gort <- lme(Volume ~ GORT_FLUENCY+AGE, 
>  random = ~ 1 | UID,
> data=df, na.action=na.omit), error=function(err) tag <<-1)
>      data.frame(Term = rownames(anova(lme.gort)), anova(lme.gort))
> +  }
>   models = list()
>   models$anova = ddply(vol_data, c("INDEX1"), fit_vol_model1)
>   summary(lme.gort)
  The rules according to which lme calculates degress of freedom
are on p. 91 of Pinheiro and Bates 2000 
(also on Google Books, <http://tinyurl.com/ntygq3>).  You should
be able to work it out from there ...  (It's not actually clear
what your question was -- are you wondering why you have different
df for different effects?)

  Follow-ups should probably go to r-sig-mixed-models <at> r-project.org