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eigenvalue of a factor is the sum of correlations (r) of each variable with that factor. This correlation is also called loading in factor analysis. Analysts can define (or “extract”) how many factors they wish to use, or they can define a statistical criterion (typically requiring each factor to have an eigenvalue of at least 1.0). The method of identifying factors is called principal component analysis (PCA). The results of PCA often make it difficult to interpret the factors, in which case the analyst will use rotation (a statistical technique that distributes the explained variance across factors). Rotation causes variables to load higher on one factor, and less on others, bringing the pattern of groups better into focus for interpretation. Several different methods of rotation are commonly used (for example, Varimax, Promax), but the purpose of this procedure is always to understand which variables belong together. Typically, for purposes of interpretation, factor loadings are considered only if their values are at least .50, and only these values might be shown in tables. Table 18.4 shows the result of a factor analysis. The table shows various items related to managerial professionalism, and the factor analysis identifies three distinct groups for these items. Such tables are commonly seen in research articles. The labels for each group (for example, “A. Commitment to performance”) are provided by the authors; note that the three groupings are conceptually distinct. The table also shows that, combined, these three factors account for 61.97 percent of the total variance. The table shows only loadings greater than .50; those below this value are not shown.6 Based on these results, the authors then create index variables for the three groups. Each group has high internal reliability (see Chapter 3); the Cronbach alpha scores are, respectively, 0.87, 0.83, and 0.88. This table shows a fairly typical use of factor analysis, providing statistical support for a grouping scheme. Beyond Factor Analysis A variety of exploratory techniques exist. Some seek purely to classify, whereas

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Evan M. Berman (Essential Statistics for Public Managers and Policy Analysts)

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PCA- (Psychological Character Assassination)
Is when someone changes from who they are and start living their lives, according to the standards of social media.
Their minds create a new personality based on what they read on social media.
They let social media people determine or decide on how they should live their lives.

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D.J. Kyos

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Permanent Court of Attribution (PCA) has

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Anonymous