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. This book provides an introduction to a psychometric approach that establishes a coherent framework for drawing reliable valid and fair inferences from ratermediated assessments thus answering the problem of inevitably fallible human ratings manyfacet Rasch measurement MFRM. Throughout the book sample data taken from a writing performance assessment are used to illustrate key concepts theoretical foundations and analytic procedures stimulating the readers to adopt the MFRM approach in their current or future professional context.