The influence of covariates on latent job performance ratings from differing sources: A mimic modeling approach

Abstract

The potential for differential functioning of performance assessments across ratings sources has gained recent research interest. This study used multiple-group confirmatory factor analysis (MGCFA) to examine whether measures of task and contextual performance are invariant across both supervisors and subordinates. As an extension, multiple indicators multiple causes modeling (MIMIC) was used to examine potential covariates of task and contextual performance ratings on latent task and contextual performance variability. Consistent with previous research, I found measurement invariance across subordinate- and supervisor ratings. Moreover, MIMIC results showed supervisor and subordinate demographic variables systematically influenced latent task and contextual performance variability despite measurement invariance over these rating sources. Implications for multi-source performance systems are discussed.