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Titlebook: Applying Test Equating Methods; Using R Jorge González,Marie Wiberg Book 2017 The Editor(s) (if applicable) and The Author(s), under exclus

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发表于 2025-3-21 19:07:21 | 显示全部楼层 |阅读模式
期刊全称Applying Test Equating Methods
期刊简称Using R
影响因子2023Jorge González,Marie Wiberg
视频video
发行地址Discusses how to perform traditional and modern equating methods within R, a platform that has grown in popularity over the last decade and which is freely available from the web.Includes the latest i
学科分类Methodology of Educational Measurement and Assessment
图书封面Titlebook: Applying Test Equating Methods; Using R Jorge González,Marie Wiberg Book 2017 The Editor(s) (if applicable) and The Author(s), under exclus
影响因子This book describes how to use test equating methods in practice. The non-commercial software R is used throughout the book to illustrate how to perform different equating methods when scores data are collected under different data collection designs, such as equivalent groups design, single group design, counterbalanced design and non equivalent groups with anchor test design. The R packages equate, kequate and SNSequate, among others, are used to practically illustrate the different methods, while simulated and real data sets illustrate how the methods are conducted with the program R. The book covers traditional equating methods including, mean and linear equating, frequency estimation equating and chain equating, as well as modern equating methods such as kernel equating, local equating and combinations of these. It also offers chapters on observed and true score item response theory equating and discusses recent developments within the equating field. More specifically it covers the issue of including covariates within the equating process, the use of different kernels and ways of selecting bandwidths in kernel equating, and the Bayesian nonparametric estimation of equating fu
Pindex Book 2017
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发表于 2025-3-21 23:02:42 | 显示全部楼层
Preparing Score Distributions,describe how to prepare the score distributions in order to read them into the different . packages that will be used. Presmoothingthe score distributions as a first step in equating is also discussed. Known data sets appearing in the equating literature, as well as real data examples from an admiss
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Kernel Equating,ets that were introduced in Chap. . and which have been previously analyzed in the literature. We also illustrate the methods using the . admissions test data set. The . packages . (Andersson et al., J Stat Softw 55(6):1–25, 2013) and . (González, J Stat Softw 59(7), 1–30, 2014) are used throughout
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Recent Developments in Equating,sson et al., J Stat Softw 55(6):1–25, 2013) and . (González, J Stat Softw 59(7):1–30, 2014). The chapter begins with recent developments within the kernel equating framework, including different bandwidth selection methods, the use of different kernels in the continuization step, andIRT kernel equat
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2367-170X t covers the issue of including covariates within the equating process, the use of different kernels and ways of selecting bandwidths in kernel equating, and the Bayesian nonparametric estimation of equating fu978-3-319-84750-4978-3-319-51824-4Series ISSN 2367-170X Series E-ISSN 2367-1718
发表于 2025-3-23 04:02:25 | 显示全部楼层
Book 2017 equating and discusses recent developments within the equating field. More specifically it covers the issue of including covariates within the equating process, the use of different kernels and ways of selecting bandwidths in kernel equating, and the Bayesian nonparametric estimation of equating fu
发表于 2025-3-23 08:11:25 | 显示全部楼层
Book 2017rm different equating methods when scores data are collected under different data collection designs, such as equivalent groups design, single group design, counterbalanced design and non equivalent groups with anchor test design. The R packages equate, kequate and SNSequate, among others, are used
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