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Viser: Generalized Kernel Equating with Applications in R

Generalized Kernel Equating with Applications in R, 1. udgave
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Generalized Kernel Equating with Applications in R Vital Source e-bog

Marie Wiberg, Jorge Gonzalez og Alina A. Von Davier
(2024)
Taylor & Francis
770,00 kr.
Leveres umiddelbart efter køb
Generalized Kernel Equating with Applications in R

Generalized Kernel Equating with Applications in R

Marie Wiberg, Jorge Gonzalez og Alina A. von Davier
(2024)
Sprog: Engelsk
CRC Press LLC
1.288,00 kr.
Denne bog er endnu ikke udgivet. Den forventes Nov 2024.

Detaljer om varen

  • 1. Udgave
  • Vital Source searchable e-book (Reflowable pages)
  • Udgiver: Taylor & Francis (November 2024)
  • Forfattere: Marie Wiberg, Jorge Gonzalez og Alina A. Von Davier
  • ISBN: 9781315283753
Generalized Kernel Equating is a comprehensive guide for statisticians, psychometricians, and educational researchers aiming to master test score equating. This book introduces the Generalized Kernel Equating (GKE) framework, providing the necessary tools and methodologies for accurate and fair score comparisons. The book presents test score equating as a statistical problem and covers all commonly used data collection designs. It details the five steps of the GKE framework: presmoothing, estimating score probabilities, continuization, equating transformation, and evaluating the equating transformation. Various presmoothing strategies are explored, including log-linear models, item response theory models, beta4 models, and discrete kernel estimators. The estimation of score probabilities when using IRT models is described and Gaussian kernel continuization is extended to other kernels such as uniform, logistic, epanechnikov and adaptive kernels. Several bandwidth selection methods are described. The kernel equating transformation and variants of it are defined, and both equating-specific and statistical measures for evaluating equating transformations are included. Real data examples, guiding readers through the GKE steps with detailed R code and explanations are provided. Readers are equipped with an advanced knowledge and practical skills for implementing test score equating methods.
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Detaljer om varen

  • Hardback: 272 sider
  • Udgiver: CRC Press LLC (November 2024)
  • Forfattere: Marie Wiberg, Jorge Gonzalez og Alina A. von Davier
  • ISBN: 9781138196988

Generalized Kernel Equating is a comprehensive guide for statisticians, psychometricians, and educational researchers aiming to master test score equating. This book introduces the Generalized Kernel Equating (GKE) framework, providing the necessary tools and methodologies for accurate and fair score comparisons.

The book presents test score equating as a statistical problem and covers all commonly used data collection designs. It details the five steps of the GKE framework: presmoothing, estimating score probabilities, continuization, equating transformation, and evaluating the equating transformation. Various presmoothing strategies are explored, including log-linear models, item response theory models, beta4 models, and discrete kernel estimators. The estimation of score probabilities when using IRT models is described and Gaussian kernel continuization is extended to other kernels such as uniform, logistic, epanechnikov and adaptive kernels. Several bandwidth selection methods are described. The kernel equating transformation and variants of it are defined, and both equating-specific and statistical measures for evaluating equating transformations are included. Real data examples, guiding readers through the GKE steps with detailed R code and explanations are provided. Readers are equipped with an advanced knowledge and practical skills for implementing test score equating methods.

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
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