Statistical Analysis for Education and Psychology Researchers

class sex subj time;

model score= sex subj(sex) time sex*time;

test h=sex e=subj (sex);

run;

Output from this code is shown in Figure 8.21.
General Linear Models Procedure
Class Level Information

(^) Class Levels Values
(^) sex 2 0 1
(^) subj 10 1 2 3 4 5 6 7 8 9 10
(^) time 3 1 2 3
Number of observations in data set=30
General Linear Models Procedure
Dependent Variable: SCORE
Source DF Sum of Squares Mean Square F Value Pr>F
Model 13 76.7000000 5.9000000 15.06 0.0001
Error 16 6.26666667 0.3916667
Corrected
Total 29 82.9666667
R-Square C.V. Root MSE SCORE Mean
0.924468 11.66148 0.62583 5.36667
Source DF Type I SS Mean Square F Value Pr>F
sex 1 9.6333333 9.6333333 24.60 0.0001
subj(sex) 8 39.3333333 4.9166667 12.55 0.0001
time 2 17.8666667 8.9333333 22.81 0.0001
sextime 2 9.8666667 4.9333333 12 .60 0.0005
Source DF Type III SS Mean Square F Value Pr>F
sex 1 9.6333333 9.6333333 24.60 0.0001
subj(sex) 8 39.3333333 4.9166667 12.55 0.0001
time 2 17.8666667 8.9333333 22.81 0.0001
sextime 2 9.8666667 4.9333333 12.60 0.0005
Tests of Hypotheses—using the Type III MS for. subj (sex) as an error term
Source DF Type III SS Mean Square F Value Pr>F
sex 1 9.63333333 9.63333333 1.96 0.1991

Figure 8.21: Output for univariate

split-plot ANOVA on the data shown in

Table 8.15

Interpretation of Computer Output

The first section of output contains the usual summary information which should be
checked to ensure the model fitted is correct. Here there are two levels for the between
subjects factor (sex), three repeated measurements over time, ten subjects and a total of

Inferences involving continuous data 341