Knowledge that Transforms

Statistical methods play an important role in salary discrimination litigation. Regression analysis is the most widely used method in this application. In regression analysis, group differences in salary are evaluated among employees who have been matched on measured “merit” variables (e.g., years of job experience). Difficulties often arise because important merit variables may be unmeasured, or because the available measures of merit are fallible. An alternative approach in this case lies in the use of several latent variable path models that have been proposed for the salary problem (Birnbaum, 1979; McFatter, 1987). The theoretical and practical implications of these models are discussed. The use of the models is illustrated in real data.

Working from an institutional perspective, this study tested hypotheses about the relationships between workplace characteristics and health care cost containment practices. The analyses show that urban location of the workplace, number of employees, and education level of the workforce are related to three different cost containment strategies: the management of utilization with traditional indemnity insurance plans; offering of alternative health insurance plans (HMOs); and employee development relative to health care consumption. Workplaces with greater proportions of black or female employees were less likely and those with older workers were more likely to engage in employee development practices. The race, gender, and age variables were not significantly related to the other strategies. Unionization was not significantly related to any of the three strategies in the multivariate model. These findings are proposed to have implications for human resource management, as well as for health care policy and reform efforts.

Using a sample of 192 Standard & Poor’s 500 firms, we examine the impact of corporate governance and ownership context on a particular instance of board entrenchment: adoption of classified board provisions. Interestingly, while increased outsider representation measured simply as a proportion of outsiders does not affect the rate of adoption, reliance on a more fine grained measure, which includes other affiliations of outsiders, results in a marginally significant influence. Moreover, it appears that reliance on a simple proportional measure is likely to distort the effects of other variables. Finally, institutional stock ownership is found to be the most significant factor associated with decreased rate of adoption.

In this experimental analysis, the effects of outcome feedback on risk propensity were assessed within the multiple-cue-probability-learning-paradigm (MCPLP). The individual decision maker in this task received outcome feedback on a decision-by-decision basis. It was hypothesized that information on his/her success or lack of success (outcome feedback) on each decision would influence the decision to risk (commit) resources. Hierarchical regression results revealed that after all other performance effects had been partialled out, current outcome feedback explained much of the commitment decision.

Working from an institutional perspective, this study tested hypotheses about the relationships between workplace characteristics and health care cost containment practices. The analyses show that urban location of the workplace, number of employees, and education level of the workforce are related to three different cost containment strategies: the management of utilization with traditional indemnity insurance plans; offering of alternative health insurance plans (HMOs); and employee development relative to health care consumption. Workplaces with greater proportions of black or female employees were less likely and those with older workers were more likely to engage in employee development practices. The race, gender, and age variables were not significantly related to the other strategies. Unionization was not significantly related to any of the three strategies in the multivariate model. These findings are proposed to have implications for human resource management, as well as for health care policy and reform efforts.

Statistical methods play an important role in salary discrimination litigation. Regression analysis is the most widely used method in this application. In regression analysis, group differences in salary are evaluated among employees who have been matched on measured “merit” variables (e.g., years of job experience). Difficulties often arise because important merit variables may be unmeasured, or because the available measures of merit are fallible. An alternative approach in this case lies in the use of several latent variable path models that have been proposed for the salary problem (Birnbaum, 1979; McFatter, 1987). The theoretical and practical implications of these models are discussed. The use of the models is illustrated in real data.

Becker and Cote (1994) found that the correlated uniqueness model outperformed the confirmatory factor analysis and direct product models for multitrait-multimethod data. The present study analyzed20 multitrait-multirater performance appraisal matrices. The correlated uniqueness model was appropriate significantly more often than in Becker and Cote5 study and the other two models performed poorly. The proportions of trait and method variance in ratings were related to several rating system characteristics such as opportunity for raters to observe ratees and basing rating dimensions on a job analysis. Performance of all three models was better with larger proportions of trait variance and smaller proportions of method variance.