An empirical Monte Carlo test of the accuracy of the correlation, covariance, and regression slope models for assessing validity generalization

Article Abstract:

An empirical Monte Carlo study with a large data base (N = 84,808) was conducted to determine the accuracy of the correlation, covariance, and regression slope models for assessing validity generalization (VG). This study has resulted in the following three major conclusions: (a) The correlation between sampling errors and population parameters appears to be close to zero, (b) when the sampling error is the only artifact, all three models do well in estimating the relevant parameters across three sample sizes and 10 different numbers of validity studies per VG study, and (c) when the the predictor reliability, criterion reliability, and range restriction are also included as artifacts, the accuracy of estimation depends on how closely the hypothetical and true distribution of artifacts match. All three models performed inadequately when the match between the two sets of distributions was poor. (Reprinted by permission of the publisher.)

Methods, Monte Carlo method, Monte Carlo methods

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Determining cutoff scores that optimize utility: a recognition of recruiting costs

Article Abstract:

A modification of Brogden's (1949) utility formula is proposed for establishing optimal cutoff scores in criterion-related validity studies. The proposed modification highlights the direct trade-off between selecting more capable applicants and the costs associated with selection and recruiting. Data from national cost-per-hire surveys are presented to illustrate the magnitude of recruiting costs relative to selection costs. In addition, an analysis of recruiting practices suggests the need to account for variable recruiting costs when establishing cutoff scores. Two examples are used to illustrate the procedure. Cutoff scores are set to maximize the utility derived from salesperson productivity and to minimize the expenses associated with accidents by truck drivers. (Reprinted by permission of the publisher.)

Employee recruitment, Test validity, Employment tests

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Predicting infrequent behavior: clarifying the impact on false-positive rates

Article Abstract:

The false-positive rate (i.e., individuals who are incorrectly identified as unqualified, ineligible, maladjusted, etc.) has been used to argue against the value of psychological tests (or other screening procedures) for various applications, including personnel selection, when base rates are low. Although this argument may have merit in certain situations, it is generally inappropriate when targeted at the use of tests for personnel selection. Flaws in the "false-positive" argument highlight the need to distinguish between absolute and relative decisions and to consider the appropriate control or comparative condition when examining the impact of a psychological test on decision errors. (Reprinted by permission of the publisher.)

Testing, Psychological tests, False positive reactions

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