An Updated Meta-Analysis of the Interrater Reliability of Supervisory Performance Ratings

• 成果类型: Article
• 署名作者: Zhou, You; Sackett, Paul R.; Shen, Winny; Beatty, Adam S.
• 署名单位: University of Minnesota System; University of Minnesota Twin Cities; York University - Canada; University of Minnesota System; University of Minnesota Twin Cities
• 刊物名称: JOURNAL OF APPLIED PSYCHOLOGY
• ISSN/ISSBN: 0021-9010
• DOI: 10.1037/apl0001174
• 发表日期: 2024
• 页码: 949-970
• 关键词: supervisory ratings; Job performance; INTERRATER RELIABILITY; Meta-analysis

摘要

Given the centrality of the job performance construct to organizational researchers, it is critical to understand the reliability of the most common way it is operationalized in the literature. To this end, we conducted an updated meta-analysis on the interrater reliability of supervisory ratings of job performance (k = 132 independent samples) using a new meta-analytic procedure (i.e., the Morris estimator), which includes both within- and between-study variance in the calculation of study weights. An important benefit of this approach is that it prevents large-sample studies from dominating the results. In this investigation, we also examined different factors that may affect interrater reliability, including job complexity, managerial level, rating purpose, performance measure, and rater perspective. We found a higher interrater reliability estimate (r = .65) compared to previous meta-analyses on the topic, and our results converged with an important, but often neglected, finding from a previous meta-analysis by Conway and Huffcutt (1997), such that interrater reliability varies meaningfully by job type (r = .57 for managerial positions vs. r = .68 for nonmanagerial positions). Given this finding, we advise against the use of an overall grand mean of interrater reliability. Instead, we recommend using job-specific or local reliabilities for making corrections for attenuation.