Generalized Kernel Equating with Applications in R

Marie Wiberg is professor in Statistics with specialty in psychometrics at Umeå University in Sweden. She is the author of more than 60 peer-review research papers and have edited nine books. Her research interests include test equating, large-scale assessments, parametric and nonparametric item response theory and educational measurement and psychometrics in general.Jorge González is associate professor at the Faculty of Mathematics, Pontificia Universidad Católica de Chile. He is author of a book and several publications on test equating. His research is focused on statistical modeling of data arising from the social sciences, particularly on the fields of test theory, educational measurement, and psychometrics.Alina A. von Davier is the chief of assessment at Duolingo, and the Founder of EdAstra Tech. She has received several awards, including the ATP’s Career Award, the AERA for signification contribution to educational measurement and research methodology award, and the NCME annual award for scientific contributions. Her research is in the field of computational psychometrics, machine learning, assessment, and education.

• Foreword Preface Part 1: Test Equating and Kernel Equating Overview 1 Introduction 2 Kernel Equating Part 2: Generalized Kernel Equating Framework 3 Presmoothing 4 Estimating Score Probabilities 5 Continuization 6 Bandwidth Selection 7 Equating 8 Evaluating the Equating Transformation Part 3: Applications 9 Examples under the EG design 10 Examples under the NEAT design Part 4: Appendix A Installing R and Reading in Data B R packages for GKE Bibliography