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E-raamat: Introduction to Many-Facet Rasch Measurement: Analyzing and Evaluating Rater-Mediated Assessments. 2nd Revised and Updated Edition

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Introduction to Many-Facet Rasch Measurement: Analyzing and Evaluating Rater-Mediated Assessments. 2nd Revised and Updated EditionSuurem pilt
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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 from rater-mediated assessments, thus answering the problem of fallible human ratings. Revised and updated throughout, the Second Edition includes a stronger focus on the Facets computer program, emphasizing the pivotal role that MFRM plays for validating the interpretations and uses of assessment outcomes.

This revised and updated Second Edition provides an introduction to the psychometric analysis and evaluation of rater-mediated assessments using many-facet Rasch measurement (MFRM). Essay rating data are used to illustrate the study of rater errors and biases and their implications for drawing reliable, valid, and fair inferences from assessment outcomes.

Arvustused

«[ ] this book covers a diverse array of both basic and important topics related to Rasch measurement, providing insights into complexities and intricacies involved in rater-mediated performance assessment. This books is highly recommended to researchers, practitioners, and other stakeholders who are interested in Rasch measurement, but only have a limited understanding of Rasch modeling. The book is also suitable for advanced learners and applied researchers who could consult advanced modeling techniques discussed in Chapters 8 and 9.»

(Chao Han, Measurement: Interdisciplinary Research and Perspectives, 2019, Vol. 17, N° 2)





«The strengths of this book are numerous. Discussing the MFRM approach in the context of language testing can make the concept of facets (raters, students, etc.) and their associated issues (e.g., rater variability) appealing to educators. The book discusses the limitations of standard approaches in reducing between-rater variation and shows how the MFRM approach can be used to regulate error proneness of human ratings that is inherent in such ratings. The authors broad perspective on psychometric argument of fair scores can be used with an eye toward equity in human ratings of students performance. The quality of the examples in the book is impressive. It provides an understanding of the potential in using the MFRM approach in the broader fields of education, human health sciences, and many other fields»

(Daeryong Seo & Husein Taherbhai, Applied Psychological Measurement, 2013, 37(2))

Preface to the First Edition 9(4)
Preface to the Second Edition 13(2)
1 Introduction
15(6)
1.1 Facets of measurement
15(4)
1.2 Purpose and plan of the book
19(2)
2 Rasch Measurement: The Basics
21(18)
2.1 Elements of Rasch measurement
21(7)
2.1.1 The dichotomous Rasch model
21(6)
2.1.1 Polytomous Rasch models
27(1)
2.2 Rasch modeling of many-facet data
28(11)
2.2.2 Putting the facets together
30(3)
2.2.2 The sample data: Essay ratings
33(3)
2.2.2 Rasch modeling of essay rating data
36(3)
3 Rater-Mediated Assessment: Meeting the Challenge
39(16)
3.1 Rater variability
39(3)
3.2 Interrater reliability
42(6)
3.2.2 The standard approach
42(1)
3.2.2 Consensus and consistency
43(2)
3.2.2 Limitations of the standard approach
45(3)
3.3 A conceptual-psychometric framework
48(7)
3.3.3 Proximal and distal facets
50(2)
3.3.3 A measurement approach
52(3)
4 Many-Facet Rasch Analysis: A First Look
55(16)
4.1 Preparing for a many-facet Rasch analysis
55(2)
4.2 Measures at a glance: The Wright map
57(3)
4.3 Defining separation statistics
60(3)
4.4 Applying separation statistics
63(4)
4.5 Global model fit
67(4)
5 A Closer Look at the Rater Facet: Telling Fact from Fiction
71(24)
5.1 Rater measurement results
71(11)
5.1.1 Estimates of rater severity
71(3)
5.1.1 Rater fit statistics
74(7)
5.1.1 Observed and fair rater averages
81(1)
5.2 Studying central tendency and halo effects
82(7)
5.2.2 Central tendency
83(3)
5.2.2 Halo
86(3)
5.3 Raters as independent experts
89(3)
5.4 Interrater reliability again: Resolving the paradox
92(3)
6 Analyzing the Examinee Facet: From Ratings to Fair Scores
95(18)
6.1 Examinee measurement results
95(2)
6.2 Examinee fit statistics
97(5)
6.3 Examinee score adjustment
102(7)
6.4 Criterion-specific score adjustment
109(4)
7 Criteria and Scale Categories: Use and Functioning
113(10)
7.1 Criterion measurement results
113(2)
7.2 Rating scale structure
115(2)
7.3 Rating scale quality
117(6)
8 Advanced Many-Facet Rasch Measurement
123(28)
8.1 Scoring formats
123(1)
8.2 Dimensionality
124(3)
8.3 Partial credit and hybrid models
127(5)
8.4 Modeling facet interactions
132(15)
8.4.4 Exploratory interaction analysis
133(7)
8.4.4 Confirmatory interaction analysis
140(7)
8.5 Summary of model variants
147(4)
9 Special Issues
151(22)
9.1 Rating designs
151(5)
9.2 Rater feedback
156(3)
9.3 Standard setting
159(4)
9.4 Generalizability theory (G-theory)
163(7)
9.5 MFRM software and extensions
170(3)
10 Summary and Conclusions
173(20)
10.1 Major steps and procedures
173(6)
10.2 MFRM across the disciplines
179(5)
10.3 Measurement and validation
184(5)
10.4 MFRM and the study of rater cognition
189(2)
10.5 Concluding remarks
191(2)
References 193(34)
Author Index 227(8)
Subject Index 235
Thomas Eckes is Head of the Psychometrics and Research Methodology Department, TestDaF Institute, University of Bochum, Germany. His research interests include language testing, multivariate data analysis, large-scale assessments, psychometric modeling of language competencies, and web-based testing.
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