Abstract
Rater bias is a substantial source of error in psychological research. Bias distorts observed effect sizes beyond the expected level of attenuation due to intrarater error, and the impact of bias is not accurately estimated using conventional methods of correction for attenuation. Using a model based on multivariate generalizability theory, this article illustrates how bias affects research results. The model identifies 4 types of bias that may affect findings in research using observer ratings, including the biases traditionally termed leniency and halo errors. The impact of bias depends on which of 4 classes of rating design is used, and formulas are derived for correcting observed effect sizes for attenuation (due to bias variance) and inflation (due to bias covariance) in each of these classes. The rater bias model suggests procedures for researchers seeking to minimize adverse impact of bias on study findings.
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