By S. Morton McPhail, Allan H. Church, Janine Waclawski
Alternative Validation Strategies is a groundbreaking compendium of the most up-tp-date learn and functional directions for time- and cost-saving possible choices to the normal try validation innovations linked to choice methods. The “state of the technology” concepts defined during this precious source may also help employers to guage the inferences drawn from their choice systems whereas supplying practices that meet stringent criminal and regulatory specifications.
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Extra info for Alternative Validation Strategies: Developing New and Leveraging Existing Validity Evidence
These scenarios include large and small organizations in both manufacturing and service and in both the public and private sectors. They include concerns about both cognitive and noncognitive individual differences. They represent many of the issues that make the selection problems faced by organizations distinct and unique, yet in some ways similar. In what way, then, are these scenarios similar? Is there a common theme here? Despite their apparent differences, the underlying dilemma these situations present for selection research is the same.
Changes in the business environment at the macro-economic level may change both budgets and the perceived need for selection of new employees at all. The research that was viewed as valuable and necessary previously may become the cost-saving budget cut in a surprisingly short time frame. Mergers, acquisitions, sales, and purchases of businesses may make the research moot or cast doubt on its continued relevance or applicability. The research that is acceptable or even allowed may be limited or changed by the intervention of third-party influences, including bargaining units and the general public (typically as represented by the media).
DEVELOPMENT OF VALIDATION EVIDENCE 15 Perhaps most ubiquitous among the scientific concerns is that of sample availability. Schmidt and Hunter (1998) pointed out that investigations of distributions of correlations have identified small sample size as a major source of error, resulting in what Guion (1987) earlier recognized as “far fewer situations where local validation studies are considered feasible” (p. 206). Other authors (such as Messick, 1989) have suggested that small sample validation studies actually provide less—and less reliable—information than that available from meta-analytic research, a view adopted in part (albeit with substantial caveat) by the Principles.