Title

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

Authors

Authors

D. J. Putka; H. Le; R. A. McCloy;T. Diaz

Comments

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Abbreviated Journal Title

J. Appl. Psychol.

Keywords

measurement design; ratings; reliability; JOB-PERFORMANCE RATINGS; PSYCHOLOGICAL-RESEARCH; SITUATIONAL INTERVIEW; SELECTION INTERVIEWS; CORRELATED ERRORS; VALIDITY; COEFFICIENTS; LEVEL; RATER; CONSEQUENCES; Psychology, Applied; Management

Abstract

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.

Journal Title

Journal of Applied Psychology

Volume

93

Issue/Number

5

Publication Date

1-1-2008

Document Type

Article

Language

English

First Page

959

Last Page

981

WOS Identifier

WOS:000259416300002

ISSN

0021-9010

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