Multivariate Experimental Clinical Research, v.12 no.2 (2006)

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    Applied Multivariate Research, v.12 no.2 (complete version)
    (Wichita State University, Department of Psychology, 2006)
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    From the Editor's desk
    (Wichita State University, Department of Psychology, 2006) Jackson, Dennis L.
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    Creating an empirical typology: A review of cluster analysis and other classification techniques
    (Wichita State University, Department of Psychology, 2006) Jones, David A.; Drummond, Christine R.; Saunders, Cory D.; Strang, John D.
    As computers have become more powerful, researchers have begun to use more and more complex multivariate statistical procedures to understand data sets. Cluster analysis has flourished in the last decade, yet its complexity and reputation as a form of "soft" statistics continues to hamper its use in many ways. This article is intended as an introduction to both the science and the art of cluster analysis to the reader who has only a basic knowledge of the technique. In addition, a working example is provided to illustrate aspects of the process of completing a cluster analysis.
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    Hierarchical cluster analysis of formal personality theorists: An empirical designation of theoretical families
    (Wichita State University, Department of Psychology, 2006) Cramer, Kenneth M., 1967-; Collins, Kandice R.
    The emphasis, de-emphasis, or no emphasis of 20 dimensional categories (e.g., unconscious processes, purposive behaviour, early development) were compared by hierarchical cluster analysis for 15 formal personality theorists (e.g., Freud, Rogers, Bandura). Results uncovered three relatively unique families of theorists with 100% reclassification: (a) Adler, Erikson, Freud, Horney, and Murray were grouped as Neo/Freudians; (b) Allport, Bandura, Jung, Kelly, and Rogers as Phenomenologists; and (c) Cattell, Dollard/Miller, Eysenck, and Skinner as Empiricists. The first of two discriminant functions was based on positive loadings from each of purposive behaviour, multiple motives, and self-concept; and successfully discriminated among all three clusters (Neo/Freudians exceeded the Phenomenologists who exceeded the Empiricists). The second function was based on positive loadings from each of developmental continuity, early development, and learning; and negative loadings from purposive behaviour, uniqueness, organismic focus, and ideal self. This function successfully discriminated between the Phenomenologists and both Empiricists and Neo/Freudians (who did not differ).
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    Validating a four-profile goal orientation solution using cluster analysis: Examining stress and attitudinal response patterns among organizational employees
    (Wichita State University, Department of Psychology, 2006) Fortunato, Vincent J.
    Although goal orientation has been conceptualized as a multi-dimensional construct, researchers typically examine the simple relationships between the different dimensions and outcome variables of interest. Recently however, Fortunato and Goldblatt (2006), using cluster analytic procedures, found that a four-cluster solution best explained variance in individuals' scores on a trichotomous measure of goal orientation, as well across a variety of dispositional and motivational variables. This investigation was designed to validate the four-cluster goal orientation solution and expand current organizational research by examining a variety of stress and attitudinal variables. Data from two work samples were collected: bank employees (N = 156) and retail customer service personnel (N = 212). A four-cluster solution similar to that observed by Fortunato and Goldblatt was the best solution across both samples. Because a profile approach is consistent with theory. I recommend that goal orientation researchers take a multi-dimensional (i.e., profile) approach when analyzing their data.