This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Google Scholar Google Scholar Articles by KAUFMAN, R. L. Search for Related Content Social Bookmarking                   What's this?

Issues in Multivariate Cluster Analysis

Some Simulation Results

University of Utah

Using a Monte Carlo simulation, the research in this article addresses two key questions about the accuracy of cluster analysis in reproducing a known true cluster model. First, how is the accuracy affected by different ways of measuring interunit similarity; in this case, different ways of using principal components analysis. Second, how is the accuracy affected by the quality of the characteristics data and by different procedures for handling missing information? The results indicate that using principal components analysis is superior to not using it and that the choice of how to utilize the principal components results may be critical. The results also indicate that the impact of data quality differences may be minimal, but that there are important differentials among the procedures for handling missing data.

CiteULike    Connotea    Del.icio.us    Digg    Reddit    Technorati    What's this?