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Study examines biographical data and Academy training performance for 4,559 Federal Aviation Administration (FAA) Air Traffic Controller Specialists collected from 1986 to 1992. Biodata measure was rationally scaled along personality factors of the Big Five and Occupational Information System (O*NET) general work activities. Study examines a linear predictor-criterion assumption made with rational and empirical scales by using evolutionary theories of personality to model a priori non-linear relationships with job and training performance among FAA candidates. Correlation and stepwise hierarchal quadratic multiple regression analyses revealed most scales had a linear relationship with Academy training performance; however, biodata scales of conscientiousness and mental processes did exhibit slight nonlinearity. High and low level of these dimensions predicted higher training and job performance than mid levels. Some sub-scales of conscientiousness showed the same pattern of results. Additionally, empirical keying of the same rational scales improved criterion-related validity over the purely rational scales and suffered less shrinkage upon cross-validation than a strict empirical key of the full biodata inventory. Implications for construct validity, theory, and practice are discussed.

The present study investigated the impact of scaling method, key developmental sample size, and criterion characteristics on the incremental validity of scored biographical information (biodata) as a predictor of subsequent performance. Biodata surveys administered to air traffic control students at the FAA Academy between 1988 and 1990 were used to generate data that was scaled using three different measurement technologies: (a) vertical percent empirical keying, (b) factor analysis, and (c) multidimensional item response theory (MIRT). The resulting biodata scale scores were combined with an ability-based selection test to predict FAA Academy performance (defined as final score and pass/fail) and air traffic field facility OJT performance (defined as certification or "wash out"). Comparisons were made between each method, for samples ranging in size from 4,568 to 100 students, regarding the amount of shrinkage between developmental and cross-validation groups, magnitudes of resulting cross-validities, and classification accuracy. The results indicated that at large sample sizes (N ≥ 1,000) the differences between methods regarding the amount of shrinkage and the magnitude of cross-validity coefficients were negligible. At smaller sample sizes the amount of shrinkage increased with the empirical key enhanced model demonstrating a greater amount than the factor analytically derived keying model. Though differences were small, the incremental factor analytic model appeared to predict eventual performance, in most of the samples, better than the empirical or MIRT methods. This study contributes to the comparative scaling biodata literature by providing guidelines for future research and practice. Another outcome is exposure of MIRT methods to the biodata research community.

The main objective of this investigation was to study the influence of sex on extreme response style as measured by a semantic differential. The previous studies led to a general hypothesis formulated as follows. Normal males and females differ from each other with regard to their mean extreme response style scores with females having the greater extreme response scores on the semantic differential.