The Basics of Item Response Theory Using R

1. Front Matter

   Pages i-xiv

   PDF

2. The Item Characteristic Curve

   • Frank B. Baker, Seock-Ho Kim

   Pages 1-15

3. Item Characteristic Curve Models

   • Frank B. Baker, Seock-Ho Kim

   Pages 17-34

4. Estimating Item Parameters

   • Frank B. Baker, Seock-Ho Kim

   Pages 35-53

5. The Test Characteristic Curve

   • Frank B. Baker, Seock-Ho Kim

   Pages 55-67

6. Estimating an Examinee’s Ability

   • Frank B. Baker, Seock-Ho Kim

   Pages 69-87

7. The Information Function

   • Frank B. Baker, Seock-Ho Kim

   Pages 89-104

8. Test Calibration

   • Frank B. Baker, Seock-Ho Kim

   Pages 105-125

9. Specifying the Characteristics of a Test

   • Frank B. Baker, Seock-Ho Kim

   Pages 127-135

10. Back Matter

    Pages 137-174

    PDF

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.

• ability parameter
• binary items
• classical test theory
• dichotomously scored
• difficulty parameter
• discrimination parameter
• guessing parameter
• information function
• invariance principle
• item characteristic curve
• item response theory
• logistic model
• maximum likelihood estimation
• one-parameter model
• probability of correct response
• Rasch model
• test calibration
• test characteristic curve
• three-parameter model
• two-parameter model

• Educational Psychology, University of Wisconsin-Madison, Madison, USA

  Frank B. Baker

• Educational Psychology, University of Georgia, Athens, USA

  Seock-Ho Kim

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.

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