Fairness in Employment Testing Validity Generalization, Minority Issues, and the General Aptitude Test Battery (1989) / Chapter Skim
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7 Validity Generalization Applied to the GATB
7 Validity Generalization Applied to the GATB
Pages 134-148
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From page 134... ...
The minimum sample size acceptable was 50, small for the statistical task of validating prediction of performance from test scores, but large in light of the difficulty of finding cooperative employers who have 50 workers in a single job. Some SATE samples, particularly in apprenticeable occupations, were considerably larger, although they often came from multiple establishments.
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From page 135... ...
At about the same time, the methodology of meta-analysis was receiving attention in mainstream psychology. USES staff saw possibilities in the work of John Hunter and Frank Schmidt, who were among the leaders in developing validity generalization, a variant of meta-analysis applied to validity coefficients, for use in personnel and industrial psychology.
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From page 136... ...
REDUCTION OF NINE APTITUDES TO COGNITIVE AND PSYCHOMOTOR FACTORS The intention of the original GATB validity research program was to identify, for each job studied, a combination of specific aptitudes and minimum levels for those aptitudes, that an applicant should attain before being referred to a job; these are the so-called SATBs prepared for each job. There are too many jobs in the U.S.
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From page 137... ...
Hunter argues that, contrary to the SATB analyses, multiple regression techniques should be used in predicting job performance from the nine GATB aptitudes, because the nine are strongly intercorrelated (Table 7-1~. However, the correlations between aptitudes, which must be known in order to apply multiple regression, are only poorly estimated in any one study, and a full multiple regression determining specific weights for each aptitude cannot estimate the weights accurately enough.
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From page 138... ...
(It should be noted that the general intelligence variable is the sum of verbal aptitude, spatial aptitude, and numerical aptitude with the computation test score removed; it is not measured independently of the others.) Predicting performance for a particular job thus can be reduced to appropriately weighting cognitive ability and psychomotor ability in a combined score for predicting performance, a much simpler task than assessing the relative weights of nine aptitudes.
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From page 139... ...
But part of the reason that GVN and SPQ are so highly correlated is that the spatial factor S is included in both G and SPQ. A more general observation is that the composites do not predict the specific aptitudes very accurately, even after adjusting for less than perfect reliability.' The question remains whether the specific aptitudes need to be included with separate weights in the regression equations for job performance, or whether the effect of each specific aptitude is captured sufficiently well by including the corresponding composite in the equations predicting job performance.
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From page 140... ...
Hunter suggests that the above table of correlations between validities supports his `'general ability theory," which would predict correlations of I between specific aptitudes in the same general ability group. He adjusts the given correlations by the reliability correction, which increases the within-block correlations to an average value of 1.09.
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From page 141... ...
If this is the way the true validities covary, then we can expect to find jobs with many different weightings appropriate for specific aptitudes. If cognitive ability and psychomotor ability were sufficient to predict job performance, then we would expect to be able to predict accurately the validities of all aptitudes for a given job by knowing the validities for these two composites.
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From page 142... ...
These collective data may be combined with specific data available for the job to develop regression equations predicting performance on the job. For jobs with no direct validity data, we would still need indicators of the specific aptitude validities for the job, such as provided by the five job families for Hunter's two-composite model.
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From page 143... ...
Not enough is known about predicting job performance to conclude quickly that two composites alone are sufficient, however convenient it is to work with only two variables in classifying jobs and constructing regression equations. THE FIVE JOB FAMILIES The question remains, what is the appropriate predictor for a job not previously studied?
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From page 144... ...
Sample Jobs in the Job Families: Family I-set-up/precision work: machinist; cabinet maker; metal fabricator; loom fixer Family II feeding/offbearing: shrimp picker; cornhusking machine operator; cannery worker; spot welder Family III synthesize/coordinate: retail food manager; fish and game warden; biologist; city circulation manager Family IV-analyze/compile/compute: automobile mechanic; radiological technician; automotive parts counterman; high school teacher Family V~opy/compare: assembler; insulating machine operator; forklift truck operator For the mean observed validities for job complexity categories, see Table 7-5. The final step in the classification system was the development of regression equations that predict job performance as a function of the cognitive, perceptual, and psychomotor composites within each job family (Table 7-61.
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From page 145... ...
The majority of the GATE studies (84 percent of workers studied for job performance) fall into job complexity categories 3 and 4, which correspond to the Job Families IV and V in the eventual VG-GATB referral protocol.
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From page 146... ...
However, differential prediction (in this usage meaning the ability to predict that an individual would have greater chances of success in certain classes of jobs and lesser chances in others, depending on the aptitude 2Since the average differences between black and white examinees are higher for GVN than for KFM, there is an advantage in terms of reducing adverse impact to retaining Job Family V, which has a relatively higher loading on KFM. However, these advantages will not be significant if referral is in order of within-group percentiles, which have the same average for blacks and whites.
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From page 147... ...
3. The categorization of all jobs into five job families on the basis of job complexity ratings derived from the DOT data-people-things job classification system fails to yield classes of jobs in which prediction of job performance is usefully advanced by weighting the composites GVN, SPQ, and KFM separately.
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From page 148... ...
48 GATE VALIDITIES ED VA~DI~ GENERALIZATION RECOMMENDATIONS 1. Since the job classification scheme currently used in the VG-GATB Referral System has not identified job groups with useful differences in predictive composites and is therefore of little value as a counseling tool, we recommend that USES continue to work to develop a richer job classification that will more effectively match people to jobs.
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