Applying Test Equating Methods: Using R (Methodology of Educational Measurement and Assessment). Cet article n’est pas disponible.
Langue : anglais
Edité par Springer, 2018
Série : Livre 4 sur 11 - Methodology of Educational Measurement and Assessment
- Livre broché
- Neuf

Vendeur : Revaluation Books, Exeter, Royaume-UniRevaluation Books
Vendeur avec une évaluation de 5 étoiles
Vendeur AbeBooks depuis 6 janvier 2003
Indisponible
Livre broché
Etat: Neuf
EUR 249,26
A propos de cet article
reprint edition. 196 pages. 9.25x6.10x0.51 inches. In Stock.
N° de réf. du vendeur 3319847503
- Titre
- Applying Test Equating Methods: Using R (Methodology of Educational Measurement and Assessment)
- Auteur
- Jorge González
- Éditeur
- Springer
- Année de publication
- 2018
- État de l'article
- Brand New
- Reliure
- Paperback
- Langue
- anglais
- ISBN à 10 chiffres
- 3319847503
- ISBN à 13 chiffres
- 9783319847504
- Poids de l'article
- 3,88 kilogrammes
- Série
- Livre 4 sur 11: Methodology of Educational Measurement and Assessment
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 functions. It also illustrates how to evaluate equating in practice using simulation and different equating specific measures such as the standard error of equating, percent relative error, different that matters and others.
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