10
SPSS ACTIVITIES
Repeated-Measures ANOVA
ACTIVITY 1 SPSS Output for a Repeated-Measures ANOVA
A researcher measured 10 subjects performing a hand–eye coordination task
under four different conditions. The conditions were: (1) dim light, little feedback; (2) moderate light, little feedback; (3) high light, little
feedback; and (4) high light, high feedback. Table 10.10
TABLE
gives the resulting data.
10.10
Data set.
Procedures and Questions
1
CONDITION
2
3
4
1
31
39
14
69
2
40
22
24
100
3
81
18
16
80
4
23
57
33
66
5
11
32
41
45
6
13
77
25
73
Click on Analyze→General Linear Model→Repeated
Measures.
7
26
46
77
36
8
29
35
73
81
Type in the Within-Subject Factor Name (e.g.,
condition).
9
42
62
12
88
10
25
71
77
40
A. Notice this is a repeated-measures design, because all 10
subjects were tested under all four conditions. The researcher administered the four different conditions in a random
order in an attempt to counter any carryover effects that
might result if all subjects completed the conditions in the
same order.
B. Analyze the data with SPSS by performing the following
commands:
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n
n
n
n
n
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Type in the Number of Levels (4).
SUBJECT
Click on Add.
Click on Define.
Move the four levels of condition from the left into the Within-Subjects
Variables box on the right. Note that this simply indicates that the repeated-measures (within subjects) factor consists of these measures.
Click on Options.
Click on Descriptive statistics in the Display window.
Click on Continue.
Click OK.
C. Notice that the output has seven portions. Some of them are important
to our interpretation, and others give very similar information. The portions are:
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Q
Within-subjects factors: Confirms your dependent variables across the
four conditions.
Descriptive statistics: Lists the means, standard deviations, and sample
sizes for each condition.
Multivariate tests: Presents a multivariate analysis of the repeated-measures design. Although this method is sometimes superior for use with
repeated-measures designs, it is beyond the scope of this text.
Mauchly’s test of sphericity: This is an important result.
Tests of within-subjects effects: This is another important result (the outcome of the test of conditions).
Tests of within-subjects contrasts: These are linear, quadratic, and cubic
tests of changes across the four conditions. We will not use them here.
Tests of between-subjects effects: No between-subjects effects exist in this
example. We will ignore this result.
1. How many degrees of freedom exist for the test of condition?
2. Interpret Mauchly’s test of sphericity.
3. Do you have to adjust the within-subjects effects to accommodate the
sphericity assumption?
4. Does a significant difference exist across the four levels of condition?
(Use  = .05.)
5. Why are the “Sig.” values different for the four different tests of within-subjects effects for (a) sphericity assumed, (b) Greenhouse–Geisser,
(c) Huynh–Feldt, and (d) lower-bound results?
6. Show how the degrees of freedom were obtained for each of the sphericity adjustments. (Hint: Epsilon values are found in the Mauchly
test box.)
7. What is the null hypothesis for this study?
8. Will you accept or reject the null hypothesis?
9. Assume that the sphericity assumption has not been met. Use the most
conservative adjustment for sphericity. What decision would you make
about the null hypothesis?
10. Describe the differences identified in the four conditions.
11. Draw a figure representing the differences among the four conditions.
ACTIVITY 2 An Experiment Using a Repeated-Measures Design
A researcher has 10 individuals complete a maximum treadmill run to exhaustion and records heart rates at three times: (a) immediately at the end of the
test; (b) 1 minute after completion; and (c) 2 minutes after completion. Table
10.11 gives the data that were collected.
Procedures and Questions
A. Enter the data into SPSS and complete a repeated-measures
ANOVA by following the steps suggested above. Answer
the following questions:
TABLE
10.11
Data set.
IMMEDIATE
POST
1 MINUTE
POST
Q 12. How many degrees of freedom exist for the test of
194
Time?
182
13. Interpret Mauchly’s test of sphericity.
168
14. If you decide to conduct the test for Time with the
most conservative adjustment to the degrees of
202
freedom, which adjustment would you use? What
175
do you conclude about the null hypothesis regarding
changes in heart rate across the three time periods?
185
15. Draw a figure representing the changes in heart
164
rate across the three Time periods. Put Time on
the horizontal axis and the heart rate (HR) values
191
on the vertical axis.
180
16. Interpret the figure you have drawn.
192
17. Look at the output labeled Tests of Within-Subjects
Contrasts. What do these results tell you about the
change in heart rates across the three Time periods?
18. Rerun the analysis, but this time select Plots in the Repeated Measures window. Then move the time factor to the Horizontal Axis
box. Click on Add, Continue, and OK. Compare the resulting figure
with the one you drew for question 4.
19. What do you conclude from this research?
2 MINUTES
POST
123
98
120
85
150
110
155
120
123
94
125
89
140
100
142
112
160
120
130
115