Dear R-ers,

I am analyzing longitudinal data using R.  My objective is to test a
relationship between a change in a variable (say X) and a change in another
variable (say y).  I have collected data at three time periods on both
variables.  I was able to run whether there was slope variability among the
teams on each of the two variables.  Thus, I ran (for each variable):

model.time.x<-lme(x ~ Time, random=1|GroupID,data=NA)
model.time.x.1< - lme(x ~ Time, random=Time|GroupID,data=NA)
anova (model.time.x,model.time.x.1)

and

model.time.y<-lme(y ~ Time, random=1|GroupID,data=NA)
model.time.y.1< - lme(y ~ Time, random=Time|GroupID,data=NA)
anova (model.time.y,model.time.y.1)

The results from the ANOVA functions above showed that the random models
were superior to the fixed models, supporting slope variability among the
teams.

In order to test the relationship between the CHANGE in these two
variables, I wanted to extract the slope coefficients for each team from
"model.time.x.1" and corresponding "model.time.y.1", and use these
coefficients in SPSS to run a simple regression.

My question is: what is the function and/or the procedure to extract the
coefficients from these models?

I thank you for your help!

Amanuel

-- 
Amanuel G. Tekleab, Ph.D.
*Board of Visitors' Fellow*
Associate Professor of Organizational Behavior
School of Business Administration
Wayne State University
304 Prentis Bldg.
Detroit, MI 48202
Phone: 313-577-9211
Fax: 313-577-5486

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