I would like to know the sum of squares for each term in my model. I used
the following call to fit the model

fit.courseCross <- lme(fixed= zGrade ~ Rep  + ISE
+P7APrior+Female+White+HSGPA+MATH+Years+Course+Course*P7APrior ,
                  random= ~1|SID,
                  data = Master.complete[Master.complete$Course != "P7A",])

and called an anova on it and get:

anova(fit.courseCross)
                numDF denDF   F-value p-value
(Intercept)         1 58161 1559.6968  <.0001
Rep                 1 58161  520.7263  <.0001
ISE                 1  6266   21.3713  <.0001
P7APrior            2 58161  358.4827  <.0001
Female              1  6266   89.2614  <.0001
White               1  6266  235.9984  <.0001
HSGPA               1  6266 1156.4116  <.0001
MATH                1  6266 1036.1354  <.0001
Years               1 58161  407.6096  <.0001
Course             12 58161   68.9875  <.0001
P7APrior:Course    24 58161   10.2464  <.0001

The documentation for anova.lme says:

When only one fitted model object is present, a data frame with the sums of
squares, numerator degrees of freedom, denominator degrees of freedom,
F-values, and P-values for Wald tests for the terms in the model (when
Terms and L are NULL), a combination of model terms (when Terms in not
NULL), or linear combinations of the model coefficients (when L is not
NULL).

noticeably absent is the sum of squares.

How do I get them?
Robert

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