CHAPTER 15 PROBLEM 15.2 For this problem, we will use the experiment presented in Chapter 15, Problem 25, p. 394 of the textbook.  For convenience, the experiment is repeated here. A university researcher knowledgeable in Chinese medicine conducted a study to determine whether acupuncture can help reduce cocaine addiction.  In this experiment, 18 cocaine addicts were randomly assigned to one of three groups of 6 addicts per group.  One group received 10 weeks of acupuncture treatment in which the acupuncture needles were inserted into points on the outer ear where stimulation is believed to be effective.  Another group, a placebo group, had acupuncture needles inserted into points on the ear where stimulation is known not to be effective.  The third group received no acupuncture treatment; instead, addicts in this group received relaxation therapy.  All groups also received counseling over the 10-week treatment period.  The dependent variable was craving for cocaine as measured by the number of cocaine urges experienced by each addict in the last week of treatment.  The following are the results. Acupuncture + Counseling Placebo + Counseling Relaxation + Counseling 4 7 6 5 2 3 8 12 11 8 10 7 12 7 9 6 11 6 Use SPSS to do a one-way independent groups ANOVA on the data, with a = 0.05 to determine if at least one of the groups differs significantly from at least one of the other groups.  Do a planned comparison between the Acupuncture + Counseling group and the Placebo + Counseling group, using α = 0.052 tail.  If the one-way ANOVA yields significant results, do the Tukey HSD post hoc test to see which groups differ from each other, again using α = 0.052 tail. If you choose to enter the data by typing it into the Data Editor, name the variables, “Group” and “Urges.”  The saved data file for this problem is “Ch15prob2.” See Solution Below. SOLUTION Step 1: Enter and Name the Data.  As usual, you have three choices for entering the data: 1) by typing the scores directly into the Data Editor; 2) by downloading from the web the saved data file for this example, and 3) by opening the saved data file (for this example) that resides on your computer.  Entering the scores by typing them directly into the Data Editor.  If you choose to type in the data, remember to name the grouping variable Group and the other variable Urges .  If you have any questions, please follow the instructions in Illustrative Example 1 for Chapter 15, substituting the variables and scores for this problem. Entering the scores by downloading from the web, the saved data file for this example.  To enter the scores using this option, click here , and then click Open from the drop-down menu.   Entering the scores by opening the saved data file (for this example) that resides on your computer .   If you choose to open the saved data file, the name of the file is Ch15prob2 .  To enter the data and name the variables for this problem,.

1. CHAPTER 15
PROBLEM 15.2
For this problem, we will use the experiment presented in
Chapter 15, Problem 25, p. 394 of the textbook. For
convenience, the experiment is repeated here.
A university researcher knowledgeable in Chinese medicine
conducted a study to determine whether acupuncture can help
reduce cocaine addiction. In this experiment, 18 cocaine
addicts were randomly assigned to one of three groups of 6
addicts per group. One group received 10 weeks of acupuncture
treatment in which the acupuncture needles were inserted into
points on the outer ear where stimulation is believed to be
effective. Another group, a placebo group, had acupuncture
needles inserted into points on the ear where stimulation is
known not to be effective. The third group received no
acupuncture treatment; instead, addicts in this group received
relaxation therapy. All groups also received counseling over
the 10-week treatment period. The dependent variable was
craving for cocaine as measured by the number of cocaine urges
experienced by each addict in the last week of treatment. The
following are the results.
Acupuncture +
Counseling
Placebo +
Counseling
Relaxation +

2. Counseling
4
7
6
5
2
3
8
12
11
8
10
7
12
7
9
6
11

3. 6
Use SPSS to do a one-way independent groups ANOVA on the
data, with
a
= 0.05 to determine if at least one of the groups differs
significantly from at least one of the other groups. Do a
planned comparison between the Acupuncture + Counseling
group and the Placebo + Counseling group, using
α
= 0.052 tail. If the one-way ANOVA yields significant results,
do the Tukey HSD post hoc test to see which groups differ from
each other, again using
α
= 0.052 tail.
If you choose to enter the data by typing it into the Data Editor,
name the variables, “Group” and “Urges.” The saved data file
for this problem is “Ch15prob2.”
See
Solution
Below.
SOLUTION
Step 1:
Enter and Name the Data.

4. As usual, you have three choices for entering the data: 1) by
typing the scores directly into the Data Editor; 2) by
downloading from the web the saved data file for this example,
and 3) by opening the saved data file (for this example) that
resides on your computer.
Entering the scores by typing them directly into the Data Editor.
If you choose to type in the data, remember to name the
grouping variable
Group
and the other variable
Urges
. If you have any questions, please follow the instructions in
Illustrative Example 1 for Chapter 15, substituting the variables
and scores for this problem.
Entering the scores by downloading from the web, the saved
data file for this example. To enter the scores using this option,
click
here
, and then
click
Open

5. from the drop-down menu.
Entering the scores by opening the saved data file (for this
example) that resides on your computer
.
If you choose to open the saved data file, the name of the file
is
Ch15prob2
. To enter the data and name the variables for this problem,
please follow the instructions in Illustrative Example 1 for
Chapter 15.
When the data are entered and named correctly, the Data Editor,
Data View should look like Figure 15.2.1.
Figure 15.2.1. Data Editor with
Group
and
Urges
scores entered.
Step 2:
Conclusion Regarding the Overall Effect of the Independent

6. Variable, using α = 0.05 Plus Planned and Post Hoc
Comparisons
.
The appropriate test to evaluate the overall effect of the
independent variable is the One-Way Analysis of Variance. To
have SPSS do the analysis using this test,
Click
Analyze
.
Select
Compare Means
.
Click
One-Way ANOVA…
.
Click
the ►
button

7. for the
F
actor:
box.
Click
Urges
in the large box on the left.
Click
the ►
button
for the
D
e
pendent List:
box.
Click
the
O
ptions button.
Click

8. D
escriptive
.
Click
Continue
.
Click
C
ontrasts…
.
Type
1
in the
Coefficients:
box
.
Click

9. A
dd
.
Type
-1
in the
Coefficients:
box.
Click
A
dd
.
Type
0
in the
Coefficients:
box.

10. Click
A
dd
.
Click
Continue
.
Click
the
Post Hoc… button
at the bottom-middle of the dialog box.
Click
T
ukey
.
Click
Continue

11. .
Click
OK
.
This produces a drop-down menu.
This also produces a drop-down menu.
This produces the
One-Way ANOVA
dialog box with
Group
highlighted.
This moves
Group
into the
F
actor:
box.
This highlights

12. Urges
.
This moves
Urges
into the
D
e
pendent List:
box.
This produces the
One-Way ANOVA: Options
dialog box.
This puts a
P
in the
D
escriptive
box, telling SPSS to compute some descriptive statistics and
include them in the output.
This returns you to the
One-Way ANOVA

13. dialog box. You have finished telling SPSS what it needs to
know to do the
One-Way ANOVA
. Let’s now implement the planned comparisons analysis. We
will follow this with the Tukey
post hoc
analysis.
This produces the
One-Way ANOVA: Contrasts
dialog box. The coefficients for doing planned comparisons
are entered in this dialog box. Since you are asked to do a
planned comparison between the Acupuncture + Counseling
group (Group 1, according to our assignment of grouping values
in the Data Editor) and the Placebo + Counseling group (Group
2) the correct coefficients for this planned comparison are 1 -1
0. Alternately, we could use -1 1 0. Let’s use 1 -1 0.
This moves the
1
into the large box below the
Coefficients:
box
.

14. This moves the
-1
into the large box below the
Coefficients:
box
.
This moves the
0
into the large box below the
Coefficients:
box. You have finished entering the planned comparison,
1 -1 0
.
This returns you to the
One-Way ANOVA
dialog box. You are now ready to implement doing the Tukey
HSD
post hoc
test.
This produces the
One-Way ANOVA: Post Hoc Multiple Comparisons
dialog box.

15. This puts a
P
in the
T
ukey
box and tells SPSS to do the Tukey HSD test when you give it
the OK.
This returns you to the
One-Way ANOVA
dialog box.
SPSS analyzes the
Stress
data and outputs the results to the Viewer. The output is shown
below in Figure 15.2.2.
Figure 15.2.2. Results of

16. One-Way ANOVA
analysis including planned and post hoc testing.
The SPSS viewer shows six tables, the
Descriptives
table, the
ANOVA
table, the
Contrasts Coefficients
table, the
Contrasts Tests
table, the
Multiple Comparisons
table, and the
Stress
table. The
ANOVA
table is the table we use to conclude about the overall effect of
the independent variable. This table shows that
F
obt
=
8.543
and the obtained probability is
.003

17. . Since
.003
< 0.05, your conclusion is to reject
H
0. The three treatments are not equal in their effect on cocaine
urges.
The
Contrasts Coefficients
table and the
Contrasts Tests
table pertain to the planned comparisons. There is only one
planned comparison, the comparison between the Acupuncture +
Counseling group and the Placebo + Counseling group
(coefficients 1 -1 0). The
Contrasts Tests
table gives the results of this planned comparison. We are
interested in the
Assume equal variances
part of the table. For this planned comparison (contrast 1),
to
bt
=
-3.866
with an obtained probability of

18. .0022 tailed
. Since
.002
< 0.05, you reject
H
0. It appears that Acupuncture + Counseling has a greater
effect on reducing cocaine urges than Placebo + Counseling.
The
Multiple Comparisons
table gives the results of the Tukey HSD
post hoc
test. The comparison between Group 1 and Group 2 yielded an
obtained probability value of
.004
; the comparison between Group 1 and Group 3 yielded an
obtained probability value of
.016
; and the comparison between Group 2 and Group 3 yielded an
obtained probability value of
.786
. Thus, you can reject
H
0 using
α

19. = 0.05 for the Group 1 – Group 2 comparison, and the Group 1
– Group 3 comparison, but not for the comparison between
Group 2 and Group 3. Thus, Acupuncture + Counseling
significantly reduced cocaine urges compared to both Placebo +
Counseling and Relaxation Therapy + Counseling, but you can’t
affirm that Relaxation Therapy + Counseling does better than
Placebo + Counseling. Again the planned comparison
probability is lower than the post hoc comparison probability
(.002 verses .004).