رکورد قبلیرکورد بعدی

" Using R for item response theory model applications / "


Document Type : BL
Record Number : 842121
Main Entry : Paek, Insu, (Professor of measurement and statistics)
Title & Author : Using R for item response theory model applications /\ Insu Paek and Ki Cole.
Publication Statement : Abingdon, Oxon ;New York, NY :: Routledge,, 2020.
: , ©2020
Page. NO : 1 online resource (viii, 271 pages) :: illustrations (black and white)
ISBN : 1351008137
: : 1351008145
: : 1351008153
: : 1351008161
: : 9781351008136
: : 9781351008143
: : 9781351008150
: : 9781351008167
: 1138542784
: 1138542792
: 9781138542785
: 9781138542792
Bibliographies/Indexes : Includes bibliographical references and index.
Contents : Introduction -- Unidimensional IRT with dichotomous item responses -- Unidimensional IRT with polytomous item responses -- Unidimensional IRT for other applications -- Multidimensional IRT for simple structure -- Multidimensional IRT for bifactor structure -- Limitations and caveat.
Abstract : Item response theory (IRT) is widely used in education and psychology and is expanding its applications to other social science areas, medical research, and business as well. Using R for Item Response Theory Model Applications is a practical guide for students, instructors, practitioners, and applied researchers who want to learn how to properly use R IRT packages to perform IRT model calibrations with their own data. This book provides practical line-by-line descriptions of how to use R IRT packages for various IRT models. The scope and coverage of the modeling in the book covers almost all models used in practice and in popular research, including: dichotomous response modeling polytomous response modeling mixed format data modeling concurrent multiple group modeling fixed item parameter calibration modelling with latent regression to include person-level covariate(s) simple structure, or between-item, multidimensional modeling cross-loading, or within-item, multidimensional modeling high-dimensional modeling bifactor modeling testlet modeling two-tier modeling For beginners, this book provides a straightforward guide to learn how to use R for IRT applications. For more intermediate learners of IRT or users of R, this book will serve as a great time-saving tool for learning how to create the proper syntax, fit the various models, evaluate the models, and interpret the output using popular R IRT packages.
Subject : Item response theory.
Subject : R (Computer program language)
Subject : Item response theory.
Subject : PSYCHOLOGY / Research Methodology
Subject : PSYCHOLOGY / Statistics
Subject : R (Computer program language)
Subject : SOCIAL SCIENCE / Research
Dewey Classification : ‭150.28/7‬
LC Classification : ‭BF39.2.I84‬‭P43 2020‬
Added Entry : Cole, Ki
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