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Haertel, Edward H. – Educational Testing Service, 2013
Policymakers and school administrators have embraced value-added models of teacher effectiveness as tools for educational improvement. Teacher value-added estimates may be viewed as complicated scores of a certain kind. This suggests using a test validation model to examine their reliability and validity. Validation begins with an interpretive…
Descriptors: Reliability, Validity, Inferences, Teacher Effectiveness
Moses, Tim; Liu, Jinghua – Educational Testing Service, 2011
In equating research and practice, equating functions that are smooth are typically assumed to be more accurate than equating functions with irregularities. This assumption presumes that population test score distributions are relatively smooth. In this study, two examples were used to reconsider common beliefs about smoothing and equating. The…
Descriptors: Equated Scores, Data Analysis, Scores, Methods
Haberman, Shelby J.; Dorans, Neil J. – Educational Testing Service, 2011
For testing programs that administer multiple forms within a year and across years, score equating is used to ensure that scores can be used interchangeably. In an ideal world, samples sizes are large and representative of populations that hardly change over time, and very reliable alternate test forms are built with nearly identical psychometric…
Descriptors: Scores, Reliability, Equated Scores, Test Construction
Kane, Michael – Educational Testing Service, 2010
The 12th annual William H. Angoff Memorial Lecture was presented by Dr. Michael T. Kane, ETS's (Educational Testing Service) Samuel J. Messick Chair in Test Validity and the former Director of Research at the National Conference of Bar Examiners. Dr. Kane argues that it is important for policymakers to recognize the impact of errors of measurement…
Descriptors: Error of Measurement, Scores, Public Policy, Test Theory
Rizavi, Saba; Way, Walter D.; Davey, Tim; Herbert, Erin – Educational Testing Service, 2004
Item parameter estimates vary for a variety of reasons, including estimation error, characteristics of the examinee samples, and context effects (e.g., item location effects, section location effects, etc.). Although we expect variation based on theory, there is reason to believe that observed variation in item parameter estimates exceeds what…
Descriptors: Adaptive Testing, Test Items, Computation, Context Effect