Work sample exams are generally thought to have either low or comparatively low levels of ethnic group differences when used for personnel selection. Such exams are sometimes called "simulation exercises" and involve having applicants perform a set of tasks that are similar to those performed on the job. The nearly ubiquitous meta-analytic value of Black-White subgroup differences in the literature is d = .38. Unfortunately, this estimate is plagued by a variety of problems (e.g., range restriction, inclusion of nonwork sample tests). Further, there are virtually no analyses that examine how the saturation of different constructs influence work sample tests. We gathered available data for Black-White ethnic group differences and found that overall work sample differences were markedly larger for samples of job applicants (d = .73) than previously thought. We also examined how different exercises and saturation of different constructs influenced work sample ds. For example, work sample test ratings of cognitive and job knowledge skills were associated with a mean observed d = .80, whereas ratings of various social skills were associated with mean observed ds that varied from .21 to .27. We urge scientists and practitioners to consider both the method and the constructs that are targeted when forecasting predictor ds.

Fisher (1930) presented both theoretical and empirical results concerning genetic influences on fertility. Since then, only sparse research has been done on the genetics of fertility, although more sophisticated methodogy and data now exist than were available to Fisher. This paper presents a behavioural genetic analysis of age at first intercourse, accounting for genetic, shared environmental, and selected non-shared environmental influences. The data came from the nationally representative National Longitudinal Survey of Youth (NLSY). A newly developed kinship linking procedure was used that identifies links for cousins, half-siblings, full-siblings and twins in the NLSY. The results suggest a genetic influence in the overall dataset, and also among whites and in male–male and opposite-sex pairs. Genetic influences were extremely small or non-existent for blacks and for female–female pairs. Shared environmental influences were small for most subsets of the data, but moderate for female–female pairs. Two specific non-shared environmental influences – self-esteem and locus of control – were ruled out as accounting for any meaningful variance, although other general sources of non-shared environmental influence appear potentially important. Analysis of selected samples from upper and lower tails suggested that genetic influences are important in accounting for both early and late non-virginity. These findings are consistent with work reported by Miller et al. (1999), who used molecular genetic methods. Generally, these findings support the existence of genetic influences and implicate non-shared environmental influences as being important determinants of the timing of loss of virginity among US adolescents and young adults.

Combining/weighting subscores into an aggregate score involves issues that apply to many fields in the organizational sciences (e.g., weighting predictors in selection, weighting multiple performance appraisal indicators, overall evaluation of organizations). The weights that are used in practice can be different (differential weights) or equal (unit weights). Relevant literature across multiple disciplines and multiple decades is reviewed. The literature indicates that unit weights have substantial predictive validity when compared with regression weights, but there is a lack of data on how other differential weighting strategies (e.g., weights generated by subject matter experts) compare to unit weights. In response, a primary and a meta-analytic study are provided here. The recent literature also contains some potential criticisms of unit weights in regard to personnel selection and content validation—and those statements are evaluated. The data and findings indicate that unit weights can be a highly appropriate approach for weighting under many circumstances.

Nonlinear dynamic modeling has useful developmental applications. The authors introduce this class of models and contrast them with traditional linear models. Epidemic models of the onset of social activities (EMOSA models) are a special case, motivated by J. L. Rodgers and D. C. Rowe's (1993) social contagion theory, which predict the spread of adolescent behaviors like smoking, drinking, delinquency, and sexuality. In this article, a biological outcome, pregnancy, is added to an earlier EMOSA sexuality model. Parameters quantify likelihood of pregnancy for girls of different sexuality statuses. Five different sexuality/pregnancy models compete to explain variance in national prevalence curves. One finding was that, in the context of the authors' simplified model, adolescent girls have an approximately constant probability of pregnancy across age and time since virginity.

Hispanics are both the largest and fastest growing minority group in the U.S. workforce. Asians also make up a substantial and increasing portion of the workforce. Unfortunately, empirical research on how these groups perform selection procedures appears to be lacking. To address this critical gap, we identified and reviewed research from a variety of literatures relevant to Hispanic and/or Asian performance on 12 commonly used staffing procedures. We also contacted authors of studies that included members of these subgroups and requested the relevant data. On the basis of our review, we provide updated estimates of Hispanic-White and Asian-White differences for the predictors, which often differ from existing estimates of these differences. Further, we provide the first known meta-analytic estimates for Hispanics and Asians on many predictors, such as vocational interests and physical ability. We discuss the implications of the findings for staffing research and practice. We also identify critical next steps for future research regarding these 2 important, yet largely neglected, groups. (PsycINFO Database Record