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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