04528nam a22005535i 4500
978-981-10-3302-5
DE-He213
20181204134233.0
cr nn 008mamaa
170102s2016 si | s |||| 0|eng d
9789811033025
978-981-10-3302-5
10.1007/978-981-10-3302-5
doi
ISI Library, Kolkata
QA276-280
PBT
bicssc
MAT029000
bisacsh
PBT
thema
519.5
23
Wu, Margaret.
author.
aut
http://id.loc.gov/vocabulary/relators/aut
Educational Measurement for Applied Researchers
[electronic resource] :
Theory into Practice /
by Margaret Wu, Hak Ping Tam, Tsung-Hau Jen.
Singapore :
Springer Singapore :
Imprint: Springer,
2016.
XIV, 306 p. 114 illus., 74 illus. in color.
online resource.
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rdacontent
computer
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rdamedia
online resource
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What Is Measurement -- Construct, Framework and Test Development - from IRT Perspectives. - Test Design -- Test Administration and Data Preparation -- Classical Test Theory -- An Ideal Measurement -- Rasch Model (The Dichotomous Case) -- Residual-based Fit Statistics -- Partial Credit Model -- Two-parameter IRT Models,- Differential Item Function -- Equating -- Facets Models -- Bayesian IRT Models (MML estimation) -- Multidimensional IRT models.
This book is a valuable read for a diverse group of researchers and practitioners who analyze assessment data and construct test instruments. It focuses on the use of classical test theory (CTT) and item response theory (IRT), which are often required in the fields of psychology (e.g. for measuring psychological traits), health (e.g. for measuring the severity of disorders), and education (e.g. for measuring student performance), and makes these analytical tools accessible to a broader audience. Having taught assessment subjects to students from diverse backgrounds for a number of years, the three authors have a wealth of experience in presenting educational measurement topics, in-depth concepts and applications in an accessible format. As such, the book addresses the needs of readers who use CTT and IRT in their work but do not necessarily have an extensive mathematical background. The book also sheds light on common misconceptions in applying measurement models, and presents an integrated approach to different measurement methods, such as contrasting CTT with IRT and multidimensional IRT models with unidimensional IRT models. Wherever possible, comparisons between models are explicitly made. In addition, the book discusses concepts for test equating and differential item functioning, as well as Bayesian IRT models and plausible values using simple examples. This book can serve as a textbook for introductory courses on educational measurement, as supplementary reading for advanced courses, or as a valuable reference guide for researchers interested in analyzing student assessment data.
Mathematical statistics.
Statistics.
Educational tests and measuremen.
Computer software.
Statistical Theory and Methods.
http://scigraph.springernature.com/things/product-market-codes/S11001
Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law.
http://scigraph.springernature.com/things/product-market-codes/S17040
Assessment, Testing and Evaluation.
http://scigraph.springernature.com/things/product-market-codes/O33000
Mathematics in the Humanities and Social Sciences.
http://scigraph.springernature.com/things/product-market-codes/M32000
Mathematical Software.
http://scigraph.springernature.com/things/product-market-codes/M14042
Tam, Hak Ping.
author.
aut
http://id.loc.gov/vocabulary/relators/aut
Jen, Tsung-Hau.
author.
aut
http://id.loc.gov/vocabulary/relators/aut
SpringerLink (Online service)
Springer eBooks
Printed edition:
9789811033001
Printed edition:
9789811033018
Printed edition:
9789811098376
https://doi.org/10.1007/978-981-10-3302-5
ZDB-2-SMA
EB
Mathematics and Statistics (Springer-11649)
276147
MAIN
MAIN
2017-04-01
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EB1698
2018-12-04 00:00:00
EB
426744
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