Search

Relative weight analysis is a procedure for estimating the relative importance of correlated predictors in a regression equation. Because the sampling distribution of relative weights is unknown, researchers using relative weight analysis are unable to make judgments regarding the statistical significance of the relative weights. J. W. Johnson (2004) presented a bootstrapping methodology to compute standard errors for relative weights, but this procedure cannot be used to determine whether a relative weight is significantly different from zero. This article presents a bootstrapping procedure that allows one to determine the statistical significance of a relative weight. The authors conducted a Monte Carlo study to explore the Type I error, power, and bias associated with their proposed technique. They illustrate this approach here by applying the procedure to published data. (Contains 5 footnotes, 2 tables and 5 figures.)

The current study evaluates the measurement precision of the Abridged Big Five Circumplex (AB5C) of personality traits by identifying those items that demonstrate differential item functioning by gender and ethnicity. Differential item functioning is found in 33 of 45 (73%) of the AB5C scales, across gender and ethnic groups (Caucasian vs. African American). More differential item functioning is found by ethnic groups compared with gender groups. The amount of differential item functioning found in these personality measures suggests the need to consider differential item functioning in the construction of measures. The authors encourage those using the AB5C measure to discard or reword these problematic items. (Contains 1 figure and 6 tables.)

As many schools and departments are considering the removal of the Graduate Record Examination (GRE) from their graduate-school admission processes to enhance equity and diversity in higher education, controversies arise. From a psychometric perspective, we see a critical need for clarifying the meanings of measurement "bias" and "fairness" to create common ground for constructive discussions within the field of psychology, higher education, and beyond. We critically evaluate six major sources of information that are widely used to help inform graduate-school admissions decisions: grade point average, personal statements, resumes/curriculum vitae, letters of recommendation, interviews, and GRE. We review empirical research evidence available to date on the validity, bias, and fairness issues associated with each of these admission measures and identify potential issues that have been overlooked in the literature. We conclude by suggesting several directions for practical steps to improve the current admissions decisions and highlighting areas in which future research would be beneficial. [ABSTRACT FROM AUTHOR]

The Conditional Reasoning Test for Aggression (CRT‐A) indirectly measures the implicit motive to aggress by engaging respondents in inductive reasoning tasks. Most research involving the CRT‐A has been based on the original English version of the test with most data being collected in the United States. The purpose of the current paper is to evaluate the psychometric properties of a Dutch translation of this test and to examine if it could be used to predict measures of integrity. In the first of two studies, we evaluated the psychometric properties and measurement equivalence of the CRT‐A across US and Dutch samples. In the second study, we examined validity evidence for the Dutch version of the CRT‐A. Results from Study 1 indicated that the test was mostly equivalent across cultures (i.e. limited differential item functioning was detected). Results from Study 2 demonstrated that the Dutch version of the CRT‐A was correlated with measures of behavioral integrity and provided incremental prediction of integrity over and above traditional self‐report measures of explicit personality traits. We discuss the implications for using CRTs across different cultures and languages. [ABSTRACT FROM AUTHOR]

For years, organizational scholars have sought effective ways to evaluate the importance of predictors included in a regression analysis. Recent techniques, such as general dominance weights and relative weights, have shown great promise for guiding evaluations of predictor importance. Nevertheless, questions remain regarding how one should investigate relative importance in the presence of a multidimensional criterion variable. The purpose of this article is to extend understanding of relative importance statistics to multivariate designs. The authors review the concept of relative importance and discuss a new procedure for calculating estimates of importance in the presence of multiple correlated criteria. Finally, a published correlation matrix is reanalyzed and a Monte Carlo simulation conducted to compare the new procedure with another technique for estimating importance. Unlike canonical solutions, which are often uninterpretable, the proposed multivariate relative weights provide an intuitive index regarding the relationship between predictors and criteria. Implications for organizational researchers are discussed. Keywords: multiple regression, relative importance, relative weights, relative weight analysis, dominance analysis

To purchase or authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1744-6570.2007.00080.x Byline: JAMES M. LeBRETON (1), MICHAEL B. HARGIS (2), BRIAN GRIEPENTROG (3), FREDERICK L. OSWALD (4), ROBERT E. PLOYHART (5) Abstract: One of the most difficult tasks facing industrial-organizational psychologists is evaluating the importance of variables, especially new variables, to be included in the prediction of some outcome. When multiple regression is used, common practices suggest evaluating the usefulness of new variables by showing incremental validity beyond the set of existing variables. This approach assures that the new variables are not statistically redundant with this existing set, but this approach attributes any shared criterion-related validity to the existing set of variables and none to the new variables. More importantly, incremental validity alone fails to answer the question directly about the importance of variables included in a regression model-arguably the more important statistical concern for practitioners. To that end, the current article reviews 2 indices of relative importance, general dominance weights and relative weights, which may be used to complement incremental validity evidence and permit organizational decision makers to make more precise and informed decisions concerning the usefulness of predictor variables. We illustrate our approach by reanalyzing the correlation matrices from 2 published studies. Author Affiliation: (1)Purdue University (2)University of Central Arkansas (3)Fors Marsh Group, LLC (4)Michigan State University (5)University of South Carolina Article note: Correspondence and requests for reprints should be addressed to James M. LeBreton, Department of Psychological Sciences, Purdue University, West Lafayette, IN; lebreton@psych.purdue.edu.

Conditional reasoning is a new measurement technique used to measure cognitive biases associated with latent personality motives. The current article describes 3 studies examining 2 related measurement issues associated with conditional reasoning tests (CRTs). Study 1 examined the necessity of maintaining indirect assessment when administering CRTs. Results indicated that, compared with a control condition, 2 experimental conditions that disclosed the purpose of assessment yielded significant mean shifts on a CRT. Study 2 explored whether CRTs could be faked when the purpose of assessment was not disclosed. Results indicated that when indirect measurement was maintained, CRTs appeared to be resistant to faking. Study 3 compared scores on the Conditional Reasoning Test for Aggression across student, applicant, and incumbent samples. Results indicated no significant mean differences among these samples. Keywords: conditional reasoning, justification mechanism, faking, cognitive bias

This study used a randomized controlled design to test the pathways in basic psychological needs theory, where social relationships characterized by autonomy support, involvement, and structure foster psychological need satisfaction and well-being. Participants were recruited from a physical-activity-based youth program. A new staff training was implemented to manipulate the use of each interpersonal characteristic by program staff (N = 24 observed) and perceptions of each interpersonal characteristic, psychological needs, hope, and self-worth in youth (N = 379 surveyed pre- and postprogram). Staff in the intervention condition used greater overall observed autonomy support, involvement, and structure. Condition assignment did not lead to differences in youth perceptions, but observed staff behaviors positively predicted youth perceptions of staff and perceptions of staff positively predicted change in well-being. Findings indicate that the training manipulated how staff engaged youth, and autonomy support, involvement, and structure are useful strategies to foster well-being in youth. [ABSTRACT FROM AUTHOR]