Brian Junker's
Technical Reports Available On-Line

• A Complete list of official technical reports from the Department of Statistics.
• A reasonably up-to-date vita, in PostScript or Adobe Acrobat format, listing other technical reports and publications not available here.

2007

• Mariano, L. T. & Junker, B. W. (2007). Covariates of the Rating Process in Hierarchical Models for Multiple Ratings of Test Items. Journal of Educational and Behavioral Statistics, to appear.




• Cen, H., Koedinger, K., & Junker, B. W. (2007) Is Over Practice Necessary? – Improving Learning Efficiency with the Cognitive Tutor through Educational Data Mining. The 13th International Conference on Artificial Intelligence in Education (AIED 2007).




• Anozie, N. & Junker, B. W. (2007). "Investigating the utility of a conjunctive model in Q-matrix assessment using monthly student records in an online tutoring system". Paper presented at the 2007 Annual Meeting of the National Council on Measurement in Education Chicago IL.
• Junker, B. W. (2007). Uncertainty, Prediction, and Teacher Feedback Using an Online System That Teaches as It Assesses (PowerPoint). Symposium presentation to the 2007 Annual Meeting of the National Council on Measurement in Education, Chicago Illinois.




• Junker, B. W. (2007). Some issues and applications in cognitive diagnosis and educational data mining (PowerPoint). Keynote presentation to the 2007 Annual Meeting of the Psychometric Society, Tokyo, Japan.

2006

• Sijtsma, K. & Junker B. W. (2006). Item response theory: past performance, present developments, and future expectations. Behaviormetrika, 33, 75--102.




• Cen, H., Koedinger, K., & Junker, B. W. (2006). Learning Factors Analysis - A General Method for Cognitive Model Evaluation and Improvement. Proceedings of the 8th International Conference on Intelligent Tutoring Systems.




• Anozie, N. O. & Junker, B. W. (2006). Predicting end-of-year accountability assessment scores from monthly student records in an online tutoring system. Presented at the Workshop on Educational Data Mining at the 21st National Conference on Artificial Intelligence (AAAI 2006). Boston, USA. July 16-17, 2006.
• Ayers, E. & Junker, B. W. (2006). Do skills combine additively to predict task difficulty in eighth-grade mathematics? Presented at Workshop on Educational Data Mining at the 21st National Conference on Artificial Intelligence (AAAI 2006). Boston, USA. July 16-17, 2006.
• Junker, B. W. (2006). "Using on-line tutoring records to predict end-of-year exam scores: experience with the ASSISTments project and MCAS 8th grade mathematics". To appear in Lissitz, R. W. (Ed.), Assessing and modeling cognitive development in school: intellectual growth and standard settings. Maple Grove, MN: JAM Press.




• Crosson, A. C., Boston, M., Levison, A., Clare Matsumura, L., Resnick, L,. B., Kim Wolf, M, & Junker, B. W. (2006). Beyond Summative Evaluation: The Instructional Quality Assessment as a Professional Development Tool. CSE Report 691, National Center for Research on Evaluation, Standards and Student Testing (CRESST), University of Los Angeles, Los Angeles, CA.
• Clare Matsumura, L., Slater, S. C., Junker, B. W., Peterson, M., Boston, M., Steele, M., and Resnick, L. B. (2006). Measuring Reading Comprehension and Mathematics Instruction in Urban Middle Schools: A Pilot Study of the Instructional Quality Assessment. CSE Report 681, National Center for Research on Evaluation, Standards and Student Testing (CRESST), University of Los Angeles, Los Angeles, CA.
• Junker, B. W., Weisberg, Y., Clare Matsumura, L., Crosson, A., Kim Wolf, M., Levison, A., and Resnick, L. B. (2006). Overview of the Instructional Quality Assessment. CSE Report 671, National Center for Research on Evaluation, Standards and Student Testing (CRESST), University of Los Angeles, Los Angeles, CA.
• Clare Matsumura, L., Slater, S. C., Kim Wolf, M., Crosson, A., Levison, A., Peterson, M., Resnick, L. B., and Junker, B. W. (2006). Using the Instructional Quality Assessment Toolkit to Investigate the Quality of Reading Comprehension Assignments and Student Work. CSE Report 669, National Center for Research on Evaluation, Standards and Student Testing (CRESST), University of Los Angeles, Los Angeles, CA.

2005

• Cen, H., Koedinger, K., and Junker, B. W. (2005). Automating Cognitive Model Improvement by A* Search and Logistic Regression. pp. 47--53, in Beck. J. E. (ed.) Educational Data Mining: Papers from the 2005 AAAI Workshop. American Association for Artificial Intelligence, Menlo Park, California.

2004

• Weaver, R., & Junker, B. W. (2004). Model specification for cognitive assessment of proportional reasoning. Department of Statistics Technical Report \#777. Carnegie Mellon University, Pittsburgh PA. [Alt title: Investigating the foundations of a cognitively diagnostic assessment through both traditional psychometric and skills-based measurement models]




• Junker, B. W., Matsumura, L. C., Crosson, A., Wolf, M. K., Levison, A., Weisberg, Y, and Resnick, L. B. (2004). Overview of the Instructional Qualirty Assessment. Symposium paper presented at the 2004 Annual Meeting of the American Educational Research Associaation. San Diego CA.

2003

• Johnson, M. S. and Junker, B. W. (2003). Using data augmentation and Markov chain Monte Carlo for the estimation of unfolding response models. Journal of Educational and Behavioral Statistics, 28, 195--230.




• Mostow, J., Aist, G. , Burkhead, P., Corbett, A., Cuneo, A., Eitelman, S., Huang, C., Junker. B., Sklar, M.B., and Tobin, B. (2003). Evaluation of an automated Reading Tutor that listens: Comparison to human tutoring and classroom instruction (MS Word). Journal of Educational Computing Research, 29, 61--117. Preprint at http://www.cs.cmu.edu/~listen/pubs.html

2002

• Patz, R. J., Junker, B. W., Johnson, M. S., and Mariano, L. T. (2002). The Hierarchical Rater Model for Rated Test Items and its Application to Large-Scale Educational Assessment Data Journal of Educational and Behavioral Statistics, 27 341--384.
• Link to Skeletal code for fitting the HRM model of Mariano (2002 Dissertation). See also tech report by Patz, Junker and Johnson below, and the published paper "The Hierarchical Rater Model for Rated Test Items and its Application to Large-Scale Educational Assessment Data, by Patz, Junker, Johnson and Mariano (J. Ed. Beh. Stat., Dec 2002).
  
  
  Please see the README file. This is research level experimental code, and no guarantees of fitness can be made.
  
  Final versions of this code, with instructions for use, will be made avaliable on StatLib shortly.

2001

• Junker, B. W. (2001). Monotonicity and conditional independence in models for student assessment and attitude measurement. Invited working paper to accompany presentation at the HSSS Workshop on Stochastic Systems for Individual Behaviors, Louvain-la-Neuve, Belgium, 22--24 January 2001.
• Baxter, G. and Junker, B. W. (2001). Designing Developmental Assessments: A Case Study in Proportional Reasoning. Paper presented at the Annual Meeting of the National Council of Measurement in Education, April 2001, Seattle, WA.

2000

• Nonparametric IRT in Action. Brian W. Junker and Klaas Sijtsma (12/00) in Postscript or pdf (adobe acrobat) format.

• Cognitive assessment models with few assumptions, and connections with nonparametric IRT. Brian W. Junker and Klaas Sijtsma (12/00) in Postscript or pdf (adobe acrobat) format.

• Monotonicity and conditional independence in models for student assessment and attitude measurement Brian W. Junker (12/00) in Postscript or pdf (adobe acrobat) format.

• Finding improvements in student models for intelligent tutoring systems via variable selection for a linear logistic test model (presented at the Annual North American Meeting of the Psychometric Society, Vancouver, BC, Canada). Brian W. Junker, Ken Koedinger and Mario Trottini (7/00) in Postscript only.

• 712 The Hierarchical Rater Model for Rated Test Items and its Application to Large-Scale Educational Assessment Data Richard J. Patz, Brian W. Junker and Matthew S. Johnson (5/00)

• 710 Some Topics in Nonparametric and Parametric IRT, with Some Thoughts About the Future Brian W. Junker (4/00)

1999

• Some statistical models and computational methods that may be useful for cognitively-relevant assessment. Brian Junker 10/99; Prepared for the Committee on the Foundations of Assessment, National Research Council.

• 690 Measuring Appropriability in Research and Development with Item Response Models Matthew Johnson, Wesley Cohen and Brian Junker 2/99

• 688 Classical Multi-level and Bayesian Approaches to Population Size Estimation Using Multiple Lists Stephen E. Fienberg, Matthew S. Johnson and Brian W. Junker 2/99. See also the talk presented October 20, 1998 at the Royal Statistical Society Conference on Applications of Random Effects/Multilevel Models to Categorical Data in Social Sciences and Medicine.

1998

• Invited talks given in the Summer Predoctoral Internship Program at Educational Testing Service, Princeton NJ, July 6--10, 1998.
• A view of nonparametric item response theory (PostScript)
  Brian W. Junker
• Latent and manifest monotonicity in item response theory (PostScript)
  Brian W. Junker and Klaas Sijtsma
• A generic approach to MCMC in IRT (PostScript)
  Brian W. Junker
• Some thoughts about raters and parametric item response theory (PostScript)
  Brian W. Junker and Richard J. Patz
• Some issues in item response modeling of multiple recapture census problems (PostScript)
  Brian W. Junker

1997

• 670 Applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses Richard J. Patz and Brian W. Junker, 12/97

• 661 Latent and manifest monotonicity in item response models. Brian W. Junker and Klaas Sijtsma, 8/97. See also the Talk (PostScript) presented June 29, 1997 at the North American Meeting of the Psychometric Society, Gatlinburg, Tennessee.

• 658 A straightforward approach to Markov Chain Monte Carlo methods for item response models. Richard J. Patz and Brian W. Junker , 6/97

• Discussion (PostScript) of Val Johnson's Alternatives to GPA-based Evaluation of Student Performance (PostScript) for Statistical Science. Brian W. Junker and Eric T. Bradlow, 2/97

• From psychometrics through item response theory to complex statistical analyses. To be presented in Inivited Paper Meeting 69 of the 51st Session of the International Statistical Institute 18 - 26 August 1997 Istanbul, Turkey. Brian W. Junker, 3/97

1996

• 644 Analyzing Small Psychological Experiments with Item Response Models. Richard J. Patz, Brian W. Junker, F. Javier Lerch and Brian R. Huguenard , 2/96

• 643 Some remarks on Scheiblechner's treatment of ISOP models. Brian W. Junker , 2/96

• Presentations at NCME (PostScript), New York, April 1996, and the Psychometric Society (PostScript), Banff, June 1996 on EDA for response category order in polytomous item response data.

1995

• Review (PostScript) of "Statistical factor analysis and related methods," by Alexander Basilevsky; Wiley (1994). Brian W. Junker The final version appears in Applied Psychological Measurement, 18, 385--388 (1995).

• Discussion (PostScript) of "Modeling Mortality Rates for Elderly Heart Attack Patients: Profiling Hospitals in the Cooperative Cardiovascular Project" by Normand, Glickman and Ryan. Third Workshop on Bayesian Statistics in Science and Technology: Case Studies in Economics, Finance, and Business, Pittsburgh, PA. October 5--7, 1995. Stephen E. Fienberg, Martin S. Gaynor, and Brian W. Junker.

• 614 A Characterization of Monotone Unidimensional Latent Variable Models Brian W. Junker and Jules L. Ellis , 2/95 (revised 3/96). The final version appears in Annals of Statistics, 25, 1327--1343 (1997).

• Tail-measurability in montone latent variable models. Jules L. Ellis and Brian W. Junker (PostScript), 6/96. To appear, Psychometrika.

1994

• 597 A Survey of Theory and Methods of Invariant Item Ordering Klaas Sijtsma and Brian W. Junker, 5/94. The final version appears in British Journal of Mathematical and Statistical Psychology, 49, 79--105 (1996).

• Invited talks given at the 10th Annual Workshop on Item Response Theory Modeling, University of Twente (November 9-11, 1994, Enschede, The Netherlands). Brian W. Junker
• Some Applications and Perspectives on Item Response Modeling (PostScript)
• A View of Nonparametric Item Response Theory (PostScript)
• Inference, Robustness and Essential Unidimensionality (PostScript)
• A Characterization of Monotone Unidimensional Latent Variable Models (PostScript)

1992

• ca.ps Conditional Association, Essential Independence, and Monotone Unidimensional Latent Variable Models, Brian W. Junker, 6/92, (PostScript). The final version appears in Annals of Statistics, 21, 1359--1378 (1993).

Brian Junker                    (412) 268 - 8873
Department of Statistics        brian@stat.cmu.edu
232 Baker Hall                  FAX: (412) CMU-STAT
Carnegie Mellon University        or (412) 268-7828
Pittsburgh PA 15213 USA