Twenty factors identified through a factor analysis of a 102-item biographical inventory were used as predictors in a multiple regression equation to predict on-the-job performance (supervisory ratings) of oil field employees. This yielded a multiple R of .41. A total of 295 subjects participated in the study. Cross-validation yielded a correlation coefficient of .06. The t-test analyses of the factor means of equipment operators and field mechanics proved that two factors could discriminate between the groups, Mechanical Experience (p<.01) and Social Orientation (p<.05). The results of this study indicate that conducting a factor analysis of unvalidated biographical items and attempting …
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Twenty factors identified through a factor analysis of a 102-item biographical inventory were used as predictors in a multiple regression equation to predict on-the-job performance (supervisory ratings) of oil field employees. This yielded a multiple R of .41. A total of 295 subjects participated in the study. Cross-validation yielded a correlation coefficient of .06. The t-test analyses of the factor means of equipment operators and field mechanics proved that two factors could discriminate between the groups, Mechanical Experience (p<.01) and Social Orientation (p<.05). The results of this study indicate that conducting a factor analysis of unvalidated biographical items and attempting to predict performance would be less appropriate than factor analyzing predictive items to gain an understanding of their underlying dimensions.
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