Abstract
This article is a pedagogical piece on hierarchical cluster analysis, a method for investigating the structure underlying data. Such methods are useful for finding similar groups of cases in data sets when it is not known a priori how many groups are present. The article is laid out as follows: First, a brief history and overview of the methods is presented; second, an illustrative example with a small hypothetical data set is used to clarify fundamental concepts; third, hierarchical cluster analysis is applied to a data set from the author’s own program of research to illustrate one way in which the methods may be employed in nursing research; fourth, the limitations of the methods are discussed; and finally, a list of suggested readings, at varying levels of detail, are provided for the interested researcher.

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