Ill-structured measurement designs in organizational research: implications for estimating interrater reliability.

Organizational research and practice involving ratings are rife with what the authors term ill-structured measurement designs (ISMDs)--designs in which raters and ratees are neither fully crossed nor nested. This article explores the implications of ISMDs for estimating interrater reliability. The authors first provide a mock example that illustrates potential problems that ISMDs create for common reliability estimators (e.g., Pearson correlations, intraclass correlations). Next, the authors propose an alternative reliability estimator--G(q,k)--that resolves problems with traditional estimators and is equally appropriate for crossed, nested, and ill-structured designs. By using Monte Carlo simulation, the authors evaluate the accuracy of traditional reliability estimators compared with that of G(q,k) for ratings arising from ISMDs. Regardless of condition, G(q,k) yielded estimates as precise or more precise than those of traditional estimators. The advantage of G(q,k) over the traditional estimators became more pronounced with increases in the (a) overlap between the sets of raters that rated each ratee and (b) ratio of rater main effect variance to true score variance. Discussion focuses on implications of this work for organizational research and practice.

Forced-choice assessments of personality for selection: evaluating issues of normative assessment and faking resistance.

Recent research suggests multidimensional forced-choice (MFC) response formats may provide resistance to purposeful response distortion on personality assessments. It remains unclear, however, whether these formats provide normative trait information required for selection contexts. The current research evaluated score correspondences between an MFC format measure and 2 Likert-type measures in honest and instructed-faking conditions. In honest response conditions, scores from the MFC measure appeared valid indicators of normative trait standing. Under faking conditions, the MFC measure showed less score inflation than the Likert measure at the group level of analysis. In the individual-level analyses, however, the MFC measure was as affected by faking as was the Likert measure. Results suggest the MFC format is not a viable method to control faking.