Generalized Kernel Equating with Applications in R
Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences;
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Product details:
- Edition number 1
- Publisher Chapman and Hall
- Date of Publication 1 November 2024
- ISBN 9781138196988
- Binding Hardback
- No. of pages272 pages
- Size 234x156 mm
- Weight 453 g
- Language English
- Illustrations 25 Illustrations, black & white; 9 Illustrations, color; 25 Line drawings, black & white; 9 Line drawings, color; 9 Tables, black & white 659
Categories
Short description:
Generalized Kernel Equating is a comprehensive guide for those 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.
MoreLong description:
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.
MoreTable of Contents:
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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