Human ratings are subject to various forms of error and bias. Since the early days of performance assessment, this problem has been sizeable and persistent. For example, expert raters evaluating the quality of an essay, an oral communication, or a work sample, often come up with different ratings for the very same performance. In cases like this, assessment outcomes largely depend upon which raters happen to provide the rating, posing a threat to the validity and fairness of the assessment...

Since the early days of performance assessment, human ratings have been subject to various forms of error and bias. Expert raters often come up with different ratings for the very same performance and it seems that assessment outcomes largely depend upon which raters happen to assign the rating. This book provides an introduction to many-facet Rasch measurement (MFRM), a psychometric approach that establishes a coherent framework for drawing reliable, valid, and fair inferences fr...