LEADER 05563nam 22006735 450 001 9910254308703321 005 20220627164456.0 010 $a3-319-54205-2 024 7 $a10.1007/978-3-319-54205-8 035 $a(CKB)3850000000027364 035 $a(DE-He213)978-3-319-54205-8 035 $a(MiAaPQ)EBC6315716 035 $a(MiAaPQ)EBC5596106 035 $a(Au-PeEL)EBL5596106 035 $a(OCoLC)985361538 035 $a(PPN)200512927 035 $a(EXLCZ)993850000000027364 100 $a20170425d2017 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 14$aThe Basics of Item Response Theory Using R /$fby Frank B. Baker, Seock-Ho Kim 205 $a1st ed. 2017. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2017. 215 $a1 online resource (XIV, 174 p. 35 illus., 1 illus. in color.) 225 1 $aStatistics for Social and Behavioral Sciences,$x2199-7357 311 $a3-319-54204-4 320 $aIncludes bibliographical references and index. 327 $aIntroduction -- 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. 330 $aThis 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 familiar with 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. Combines clearly written text and succinct R code Utilizes a building-block approach from simple to complex, enabling readers to develop a clinical feel for item response theory and how its concepts are interrelated Includes downloadable R functions that implement various facets of item response theory 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. 410 0$aStatistics for Social and Behavioral Sciences,$x2199-7357 606 $aStatistics 606 $aAssessment 606 $aPsychometrics 606 $aR (Computer program language) 606 $aStatistics for Social Sciences, Humanities, Law$3https://scigraph.springernature.com/ontologies/product-market-codes/S17040 606 $aAssessment, Testing and Evaluation$3https://scigraph.springernature.com/ontologies/product-market-codes/O33000 606 $aPsychometrics$3https://scigraph.springernature.com/ontologies/product-market-codes/Y43000 606 $aStatistical Theory and Methods$3https://scigraph.springernature.com/ontologies/product-market-codes/S11001 615 0$aStatistics. 615 0$aAssessment. 615 0$aPsychometrics. 615 0$aR (Computer program language) 615 14$aStatistics for Social Sciences, Humanities, Law. 615 24$aAssessment, Testing and Evaluation. 615 24$aPsychometrics. 615 24$aStatistical Theory and Methods. 676 $a150.287 700 $aBaker$b Frank B$4aut$4http://id.loc.gov/vocabulary/relators/aut$0287125 702 $aKim$b Seock-Ho$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910254308703321 996 $aThe Basics of Item Response Theory Using R$92174095 997 $aUNINA