Nested Designs - Scholar

The first way is to use the sums of squares and degrees of freedom computed by SAS to calculate
"by hand" the mean squares and the proper Fs.
The second way is use a TEST statement with PROC ANOVA or with PROC GLM. The TEST
statement syntax is
TEST H=numerator mean square E=denominator mean square;
where "numerator mean square" represents the factor in the model statement whose mean square
goes in the numerator, and where "denominator mean square" represents the factor in the model
statement whose mean square goes in the denominator. Another way to think of it is that "H"
stands for "Hypothesis" and "E" stands for "Error". "H=" signifies the factor about which we
wish to test a hypothesis, and "E=" signifies the factor we wish to use as an error term for the
test.
To test the first two hypotheses mentioned earlier we would use the following TEST statements.
TEST H=HYBRID E=POTS(HYBRID);
TEST H=POTS(HYBRID) E=PLANT(POTS HYBRID);
6. Conclusion
As always, the conclusion is a statement about the alternative hypothesis.
For fixed effects, the hypotheses are about unknown constant parameters, and the conclusion, as
mentioned above, would take the form
or
There is/is not significant statistical evidence that hybrid affects
transpiration rate (P=__ ),
There is/is not significant statistical evidence that mean transpiration rate
differes among hybrids (P=__ ).
nested01.docx 18 4/5/2012