Statistics for the Behavioral Sciences by Frederick J. Gravetter, Larry B. Wallnau ISBN 10: 1305504917 ISBN 13: 9781305504912

438 CHAPTER 13 | Repeated-Measures Analysis of Variance
Descriptive Statistics
Mean
Std. Deviation
N
VAR00001
VAR00002
VAR00003
5.0000
9.0000
10.0000
2.19089
2.60768
2.44949
6
6
6
Tests of Within-Subjects Effects
Measure: MEASURE_1
Source
Type III Sum
of Squares
df
Mean
Square
F
Sig.
factor 1
Sphericity Assumed
Greenhouse-Geisser
Huynh-Feldt
Lower-bound
84.000
84.000
84.000
84.000
2
1.228
1.424
1.000
42.000
68.380
58.991
84.000
19.091
19.091
19.091
19.091
.000
.004
.002
.007
Error (factor 1)
Sphericity Assumed
Greenhouse-Geisser
Huynh-Feldt
Lower-bound
22.000
22.000
22.000
22.000
10
6.142
7.120
5.000
2.200
3.582
3.090
4.400
FIGURE 13.4
Portions of the SPSS output for the repeated-measures ANOVA for the study in Example 13.1.
denominator of the F-ratio). The final box in the output (not shown in Figure 13.4) is labeled
Tests of Between-Subjects Effects and the bottom line (Error) reports the between-subjects
sum of squares and degrees of freedom (ignore the Mean Square and F-ratio which are not part
of the repeated-measures ANOVA).
FOCUS ON PROBLEM SOLVING
1. Before you begin a repeated-measures ANOVA, complete all the preliminary calculations
needed for the ANOVA formulas. This requires that you find the total for each treatment
(Ts), the total for each person (Ps), the grand total (G), the SS for each treatment condition,
and ΣX 2 for the entire set of N scores. As a partial check on these calculations, be
sure that the T values add up to G and that the P values have a sum of G.
2. To help remember the structure of repeated-measures ANOVA, keep in mind that a
repeated-measures experiment eliminates the contribution of individual differences.
There are no individual differences contributing to the numerator of the F-ratio
(MS between treatments
) because the same individuals are used for all treatments. Therefore,