User Guide

466
Chapter 32
Assumptions. The distance or similarity measures used should be appropriate for the
data analyzed (see the Proximities procedure for more information on choices of
distance an
d similarity measures). Also, you should include all relevant variables in
your analysis. Omission of influential variables can result in a misleading solution.
Because hierarchical cluster analysis is an exploratory method, results should be
treated as
tentative until they are confirmed with an independent sample.
Figure 32-1
Hierarchical cluster analysis output
11 12 .112 0 0 2
6 11 .132 0 1 4
7 9 .185 0 0 5
6 8 .227 2 0 7
7 10 .274 3 0 7
1 3 .423 0 0 10
6 7 .438 4 5 14
13 14 .484 0 0 15
2 5 .547 0 0 11
1 4 .691 6 0 11
1 2 1.023 10 9 13
15 16 1.370 0 0 13
1 15 1.716 11 12 14
1 6 2.642 13 7 15
1 13 4.772 14 8 0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Stage
Cluster
1
Cluster
2
Cluster Combined
Coefficients
Cluster
1
Cluster
2
Stage Cluster
First Appears
Next
Stage
Agglomeration Schedule
Argentina 1 1 1
Brazil 1 1 1
Chile 1 1 1
Domincan
R.
1 1 1
Indonesia 1 1 1
Austria 2 2 1
Canada 2 2 1
Denmark 2 2 1
Italy 2 2 1
Japan 2 2 1
Norway 2 2 1
Switzerland 2 2 1
Bangladesh 3 3 2
India 3 3 2
Bolivia 4 1 1
Paraguay 4 1 1
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Case
Label
4
Clusters
3
Clusters
2
Clusters
Cluster Membership