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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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樓主
發(fā)表于 2025-3-21 19:07:21 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Applying Test Equating Methods
期刊簡稱Using R
影響因子2023Jorge González,Marie Wiberg
視頻videohttp://file.papertrans.cn/161/160269/160269.mp4
發(fā)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
學(xué)科分類Methodology of Educational Measurement and Assessment
圖書封面Titlebook: Applying Test Equating Methods; Using R Jorge González,Marie Wiberg Book 2017 The Editor(s) (if applicable) and The Author(s), under exclus
影響因子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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沙發(fā)
發(fā)表于 2025-3-21 23:02:42 | 只看該作者
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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發(fā)表于 2025-3-22 05:44:59 | 只看該作者
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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發(fā)表于 2025-3-22 21:46:31 | 只看該作者
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
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發(fā)表于 2025-3-23 04:02:25 | 只看該作者
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
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發(fā)表于 2025-3-23 08:11:25 | 只看該作者
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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