The Basics of Item Response Theory Using R - Frank B. Baker, Seock-Ho Kim

The Basics of Item Response Theory Using R

Buch | Hardcover
XIV, 174 Seiten
2017 | 1st ed. 2017
Springer International Publishing (Verlag)
978-3-319-54204-1 (ISBN)
139,09 inkl. MwSt
This graduate-level textbook is a tutorial for item response theory that covers both the basics of item response theory and the use of R for preparing graphical presentation in writings about the theory. Item response theory has become one of the most powerful tools used in test construction, yet one of the barriers to learning and applying it is the considerable amount of sophisticated computational effort required to illustrate even the simplest concepts. This text provides the reader access to the basic concepts of item response theory freed of the tedious underlying calculations. It is intended for those who possess limited knowledge of educational measurement and psychometrics.
Rather than presenting the full scope of item response theory, this textbook is concise and practical and presents basic concepts without becoming enmeshed in underlying mathematical and computational complexities. Clearly written text and succinct R code allow anyone familiarwith statistical concepts to explore and apply item response theory in a practical way. In addition to students of educational measurement, this text will be valuable to measurement specialists working in testing programs at any level and who need an understanding of item response theory in order to evaluate its potential in their settings.

Frank B. Baker, Ph.D., is Professor Emeritus of the Department of Educational Psychology at the University of Wisconsin-Madison. He is author of numerous publications dealing with item response theory and statistical methodology. He received his B.S., M.S., and Ph.D. degrees from the University of Minnesota, Minneapolis.Seock-Ho Kim, Ph.D., is Professor in the Department of Educational Psychology at the University of Georgia. He is author of numerous publications in psychometrics and applied statistics and is a member of the American Educational Research Association, the American Statistical Association, the National Council on Measurement in Education, and the Psychometric Society, among other organizations. He received his B.A. from Korea University and his M.S. and Ph.D. degrees from the University of Wisconsin-Madison.

Introduction.- Getting Started.- 1. The Item Characteristic Curve.- 2. Item Characteristic Curve Models.- 3. Estimating Item Parameters.- 4. The Test Characteristic Curve.- 5. Estimating an Examinee's Ability.- 6. The Information Function.- 7. Test Calibration.- 8. Specifying the Characteristics of a Test.- Appendix A: R Introduction.- Appendix B: Estimating Item Parameters under the Two-Parameter Model with Logistic  Regression.- Appendix C: Putting the Three Tests on a Common Ability Scale: Test Equating.- References.- Index.

Erscheinungsdatum
Reihe/Serie Statistics for Social and Behavioral Sciences
Zusatzinfo XIV, 174 p. 35 illus., 1 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 450 g
Themenwelt Geisteswissenschaften Psychologie Test in der Psychologie
Mathematik / Informatik Mathematik
Sozialwissenschaften Pädagogik
Sozialwissenschaften Soziologie Empirische Sozialforschung
Schlagworte ability parameter • Assessment, Testing and Evaluation • binary items • classical test theory • dichotomously scored • difficulty parameter • discrimination parameter • Education: examinations & assessment • Education: examinations & assessment • guessing parameter • information function • Invariance Principle • item characteristic curve • Item response theory • logistic model • mathematics and statistics • maximum likelihood estimation • one-parameter model • probability & statistics • probability of correct response • Probability & statistics • Psychological testing & measurement • Psychological testing & measurement • Psychometrics • Rasch model • Social research & statistics • Social research & statistics • Statistical Theory and Methods • Statistics for Social Science, Behavorial Science, • test calibration • test characteristic curve • three-parameter model • two-parameter model
ISBN-10 3-319-54204-4 / 3319542044
ISBN-13 978-3-319-54204-1 / 9783319542041
Zustand Neuware
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