An experiment was performed to determine the extent to which individual differences in hypothesis generation could be predicted. Measures of achievement, general mental ability, and information were included with the Alternate Uses test as predictors of hypothesis-generation performance. The Alternate Uses test was the best predictor of performance. Several variants of the Alternate Uses test were also employed to isolate the components of hypothesis generation. Two components were involved: retrieval of implicit dimensions of the objects and retrieval of uses when the dimensions are explicitly provided. The latter component was much more important. The results suggest that good hypothesis generators have skills that enable them effectively to retrieve information stored in memory.
The personnel selection literature has recently included discussion of statistically based banding as a way to handle some differences in test scores when assessing job applicants. Banding uses classical test theory and an estimated standard error of measurement to create bands of individual scores, and these bands are treated as equivalent with respect to top-down selection. However, such banding operationally assumes that standard errors of measurement are homogeneous, whereas a focus on the top score logically and statistically implies the use of a conditional standard error. Other methods, such as item response theory and binomial error models, are therefore more appropriate for computing bands. Via example and analysis, the authors demonstrate that more accurately computed bands are substantially narrower under a variety of circumstances than currently computed bands. Bands as currently constructed will label an inaccurate excess of individuals as equivalent, particularly if the test is relatively easy.
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