The problem of statistically assessing cluster analysis results is discussed; several measures based on both within-group homogeneity and between-group heterogeneity are defined. Permutation distributions for these measures are defined and expressions are derived for easily calculating the parameters of these distributions. Using these measures and their respective distributions, one can test whether given clusters significantly differ from clusters which are randomly determined.
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References
1.
AnderbergM. R. (1973), Cluster Analysis for Applications.New York: Academic Press.
2.
ArnoldS. J. (1979), “A Test for Clusters,”Journal of Marketing Research, 16(November), 545–51.
3.
BellmanR. (1973), “A Note on Cluster Analysis and Dynamic Programming,”Mathematical Biosciences, 18, 314, 311–12.
4.
CormackR. M. (1971), “A Review of Classification,”Journal of the Royal Statistical Society, Series A, 134, 321–53.
5.
DardenW. R., and FlaschnerA. B. (1974), “Visual Presentation of Stimuli Defined in Hyperspace,”Journal of Marketing Research, 11(November), 456–61.
6.
DayG. S., and HeelerR. M. (1971), “Using Cluster Analysis to Improve Marketing Experiments,”Journal of Marketing Research, 8(August), 340–7.
7.
DoyleP., and HutchinsonP. (1976), “The Identification of Target Markets,”Decision Sciences, 7, 152–61.
8.
FisherW. D. (1958), “On Grouping for Maximum Homogeneity,”Journal of the American Statistical Association, 53, 789–98.
9.
FriedmanH. P., and RubinJ. (1967), “On Some Invariant Criteria for Grouping Data,”Journal of the American Statistical Association, 62, 1159–69.
10.
GravesG. W., and WhinstonA. B. (1970), “An Algorithm for the Quadratic Assignment Problem,”Management Science, 13, B387–400.
11.
HansenP., and DeLattreM. (1978), “Complete Link Cluster Analysis by Graph Coloring,”Journal of the American Statistical Association, 93, 362, 397–403.
12.
HartiganJ. (1975), Clustering Algorithms.New York: John Wiley & Sons, Inc.
13.
HubertL. (1974), “Approximate Evaluation Techniques for the Single-Limit and Complete-Link Hierarchical Clustering Procedures,”Journal of the American Statistical Association, 69, 347, 698–704.
14.
HubertL., and LevinJ. R. (1977), “Inference Models for Categorical Clustering,”Psychological Bulletin, 84, 5, 878–87.
15.
JensenR. E. (1971), “Cluster Analysis Study of Financial Performance of Selected Business Firms,”The Accounting Review, 46, 36–56.
16.
JohanssonJ., and MoinpourR. (1977), “Objective and Perceived Similarity of Pacific Rim Countries,”Columbia Journal of World Business, Winter, 65–76.
17.
KlastorinT. D., and WattsC. A., and TrivediV. (1978), A Study of the Classification of Hospitals for Prospective Reimbursement. Research Report No. 10, Office of Research and Statistics, Health Care Financing Administration, U.S. Department of H.E.W.
18.
KnoxG. (1964), “The Detection of Space-Time Interactions,”Applied Statistics, 13, 25–9.
19.
LeeH. L. (1979), “Multivariate Tests for Clusters,”Journal of the American Statistical Association, 47, 367, 708–14.
20.
LingR. F. (1973), “A Probability Theory of Cluster Analysis,”Journal of the American Statistical Association, 68, 341, 159–64.
21.
MahajanV., and JainA. K. (1978), “An Approach to Normative Segmentation,”Journal of Marketing Research, 15(August), 338–45.
22.
MantelN. (1967), “The Detection of Disease Clustering and Generalized Regression Approach,”Cancer Research, 27, 2, 209–20.
23.
MarriottF. H. C. (1971), “Practical Problems in a Method of Cluster Analysis,”Biometrics, 27, 501–14.
24.
McClainJ. O., and RaoV. (1975), “CLUSTIZE: A Program to Test for the Quality of Clustering of a Set of Objects,”Journal of Marketing Research, 12(November), 456–60.
25.
MillerG. A. (1969), “A Psychological Method to Investigate Verbal Concepts,”Journal of Mathematical Psychology, 6, 169–91.
26.
MilliganG., and MahajanV. (1980), “A Note on Procedures for Testing the Quality of a Clustering of a Set of Objects,”Decision Science, 11, 4, 669–77.
27.
OverallJ. E., and KlettC. J. (1972), Applied Multivariate Analysis.New York: McGraw-Hill, Inc.
28.
RaoM. R. (1971), “Cluster Analysis and Mathematical Programming,”Journal of the American Statistical Association, 66, 335, 622–6.
29.
RoenkerD. L., and ThompsonC. P., and BrownS. C. (1971), “Comparison of Measures for Estimation of Clustering in Free Recall,”Psychological Bulletin, 65, 1, 45–8.
30.
SchuellT. J. (1969), “Clustering and Organization in Free Recall,”Psychological Bulletin, 27, 353–74.
31.
SneathP. H. A., and SokalR. R. (1973), Numerical Taxonomy.San Francisco: W. H. Freeman and Company.
32.
VinodH. (1969), “Integer Programming and the Theory of Grouping,”Journal of the American Statistical Association, 64, 507–17.
33.
WindY. (1973), “A New Procedure for Concept Evaluation,”Journal of Marketing, 37(October), 2–11.
34.
YeomansK. A., and GolderP. A. (1975), “Futher Observations on the Stratification of Burmingham Wards by Clustering: A Riposte,”Applied Statistics, 24, 3, 345.