The assumption that job satisfaction and job performance are related has much intuitive appeal, despite the fact that reviewers of this literature have concluded there is no strong pervasive relation between these two variables. The present meta-analytic study demonstrates that (a) the best estimate of the true population correlation between satisfaction and performance is relatively low (.17); (b) much of the variability in results obtained in previous research has been due to the use of small sample sizes, whereas unreliable measurement of the satisfaction and performance constructs has contributed relatively little to this observed variability in correlations; and (c) nine research design characteristics of a study are only modestly related to the magnitude of the satisfaction-performance correlation that will be obtained. In view of these findings, some of the major substantive and research implications of the job satisfaction-job performance relation are discussed.

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This article examines the statistical correction for attenuation and the controversies surrounding the procedure. Although originally developed for test construction purposes, the correction for attenuation is also used in meta-analysis and assessments of validity generalization. Since Spearman's classic article in 1904, correct use and interpretation of the correction for attenuation has been debated. The logic of the double and single correction formulae is discussed as well as the correction producing validity coefficients greater than 1.00. Three types of misapplications and misinterpretations of the correction in published literature are presented. The article concludes with arguments pertaining to the use of the correction formula, and it attempts to sharpen the focus of issues that have led to differences of opinion about its meaning and purpose.