We examine gender wage disparities for four groups of college-educated women--black, Hispanic, Asian, and non-Hispanic white--using the National Survey of College Graduates. Raw log wage gaps, relative to non-Hispanic white male counterparts, generally exceed -0.30. Estimated gaps decline to between -0.08 and -0.19 in nonparametric analyses that…

Continuing professional development is a foundation of the student affairs field. To stay current, practitioners use a variety of methods to learn about areas that they need to master to be successful in their careers. Results of this research indicate that staff use interactive methods such as consulting with colleagues and mentoring more so than…

A new and unified approach to test equating is described that is based on log-linear models for smoothing score distributions and on the kernel method of nonparametric density estimation. The new method contains both linear and standard equipercentile methods as special cases and can handle several important equating data collection designs. An…

Methods for detecting item score patterns that are unlikely (aberrant) given that a parametric item response theory (IRT) model gives an adequate description of the data or given the responses of the other persons in the group are discussed. The emphasis here is on the latter group of statistics. These statistics can be applied when a…

Graphic statistics as developed by John Tukey have some practical benefits for precision journalists as they assist in spotting trends not as easily noted without the use of nonparametric statistics. Some especially helpful graphic statistics are: "stem-and-leaf display,""box plots,""froots," and "flogs."…

Researchers are often in a dilemma as to whether parametric or nonparametric procedures should be cited when assumptions of the parametric methods are thought to be violated. Therefore, the Kruskal-Wallis test and the ANOVA F-test were empirically compared in terms of probability of a Type I error and power under various patterns of mean…

The strategy for investigating convergent and discriminant test validity, known as the multitrait-multimethod matrix, is investigated. A nonparametric significance testing procedure is suggested and demonstrated. (JKS)

A method for studying relationships among groups in terms of categorical data patterns is described. The procedure yields a dimensional representation of configural relationships among multiple groups and a quantitative scaling of categorical data patterns for use in subsequent assignment of new individuals to the groups. (Author/CTM)

The development of a nonparametric K-sample test for equality of slopes using Puri's generalized L statistic is presented. The test is recommended when the assumptions underlying the parametric model are violated. This procedure replaces original data with either ranks (for data with heavy tails) or normal scores (for data with light tails).…

A new measure of correlation and a measure of scale are proposed which are substantially more robust than their least squares counterparts. Increased robustness may also be obtained by use of equal regression weights, or knowledge of the theoretical structure of the weights. (Author/HG)

Nonparametric statistics are often difficult to teach in introduction to statistics courses because of the lack of real-world examples. This study demonstrated how teachers can use differences in the rankings and ratings of undergraduate and graduate values to discuss: (1) ipsative and normative scaling; (2) uses of the Mann-Whitney U-test; and…

New items are being calibrated for the next generation of the computerized adaptive (CAT) version of the Armed Services Vocational Aptitude Battery (ASVAB) (Forms 5 and 6). The requirements that the items be "good" three-parameter logistic (3-PL) model items and typically "like" items in the previous CAT-ASVAB tests have…

Item response theory (IRT) has been adapted as the theoretical foundation of computerized adaptive testing (CAT) for several decades. In applying IRT to CAT, there are certain considerations that are essential, and yet tend to be neglected. These essential issues are addressed in this paper, and then several ways of eliminating noise and bias in…

When normality does not hold, nonparametric tests represent an important data-analytic alternative to parametric tests. However, the use of nonparametric tests in educational research has been limited by the absence of easily performed tests for complex experimental designs and analyses, such as factorial designs and multiple regression analyses,…