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Chapman and Hall/CRC Generalized Kernel Equating with Applications in R (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)

Name: Generalized Kernel Equating with Applications in R (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)
Brand: Chapman and Hall/CRC

History & Philosophy

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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.

Product Specifications

Brand: Chapman and Hall/CRC
Format: hardcover
ASIN: 1138196983
Category: Books > Subjects > Health, Family & Lifestyle > Psychology & Psychiatry > History & Philosophy
Domain: Amazon UK
Release Date: 01 November 2024
Listed Since: 09 July 2016

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Chapman and Hall/CRC Generalized Kernel Equating with Applications in R (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)

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