converting a t statistic to r2

The formula R2 = t2/(df+t2) applies only if a single intercept and a 
single slope are estimate with simple linear regression in something 
like B~A or B~age, but not with interaction nor quadratic term in age.

	  For further information, I just got 4 hits from 'RSiteSearch("R^2 in 
lme")', two of which seemed relevant to your question: 
"http://finzi.psych.upenn.edu/R/Rhelp02a/archive/17572.html", and 
"http://finzi.psych.upenn.edu/R/Rhelp02a/archive/34377.html".

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	  spencer graves
--

HI
 
I wonder if anyone can help.  I have a longitudinal sample of 100 subjects:
200 data points were acquired starting at different ages and at irregular
intervals (subjects have different numbers of repeated data points, so some
have only one data point).  I have been examining the relationship over time
(it is quadratic) of continuous variables A on variable B.  To model this I
have been using linear mixed models in R.  
 
B~A*age +A*I(age^2) + random term (for individual)
 
I get t values associated with A, age and A*age.
 
How (or can) the t value for A be converted to a correlation (r) or variance
value?  
 
I recall that R2 = t2/(df+t2)
 
But can this be applied to linear mixed models and what are the degrees of
freedom?
 
I hope this is reasonably clear,
 
Many thanks for any opinions
 
Philip
 

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