Diagnostic Testing, Fall 2014 (KU)


Upcoming Workshops:

Thank you for visiting my course notes. Here are some upcoming opportunities to learn from me and my colleagues in person:

WorkshopDatesLocationInstructor
Diagnostic MeasurementMay 22-25, 2017Omni Hilton Head Oceanfront Resort, Hilton Head Island, South CarolinaJonathan Templin
Introduction to Longitudinal Multilevel ModelsMay 30-June 2, 2017Omni Hilton Head Oceanfront Resort, Hilton Head Island, South CarolinaLesa Hoffman

Course Information

Instructor:Dr. Jonathan Templin
email:jtemplin@ku.edu
Office Phone:785-864-5714
Office:614 Joseph R. Pearson Hall
Office Hours:Mondays from 1pm-4pm or by appointment
Course Meeting Time:Wednesdays from 1:30pm-4:20pm
Course Meeting Location:245 Joseph R. Pearson Hall

Course Materials

Syllabus:Syllabus
Required Textbook (link to Amazon page):Rupp, A. A., Templin, J., & Henson, R. A. (2010). Diagnostic measurement: Theory, methods, and applications. New York: Guilford Press.

Schedule of Weekly Lectures

DateLecture Topic and Materials LinkReadings (See References Section for Paper Links)
August 27thIntroduction to Diagnostic TestingNone
September 3rdOverview of Diagnostic Classification ModelsRupp, Templin, and Henson (2010): Chapters 1 and 3;
Templin, Bradshaw, and Paek (in press)
September 10thAttribute SpecificationRupp, Templin, and Henson (2010): Chapter 4;
Gorin (2007)
September 17thThe Loglinear Cognitive Diagnosis Model (LCDM)Rupp, Templin, and Henson (2010): Chapter 6 p. 112-115;
Chapter 7 p. 144-158;
Henson, Templin, and Willse (2009)
September 24thDiagnostic Structural Models, Part 1Rupp, Templin, and Henson (2010): Chapter 8;
de la Torre and Douglas (2004);
Templin, Henson, Templin, and Roussos (2008)
October 1stDiagnostic Structural Models, Part 2Same as for September 24th
October 8thOther Latent Class-Based DCMsRupp, Templin, and Henson (2010): Chapters 5 and 6;
de La Torre (2011);
von Davier (2008)
October 15thThe LCDM and Other DCMs in PracticeJurich and Bradshaw (2014);
Bradshaw, Izsák, Templin, and Jacobson (2014);
Templin and Henson (2006)
October 22ndEstimating the LCDM with MCMCRupp, Templin, & Henson (2010), Chapter 11
October 29thAttribute and Attribute Profile Estimation in DCMsRupp, Templin, & Henson (2010), Chapter 10
November 5thMeasuring the Reliability of Attributes in DCMsTemplin and Bradshaw (2013)
November 12thAssessment of Model Fit in DCMsRupp, Templin, and Henson (2010): Chapter 12;
Maydeu-Olivares & Joe (2014)
November 19thEstimation of DCMs with MplusRupp, Templin, and Henson (2010): Chapter 9
December 3rdHierarchical Attribute StructuresTemplin and Bradshaw (2014a);
von Davier and Haberman (2014);
Templin and Bradshaw (2014b)
December 10thComparing DCMs and BINs: The DLM Psychometric Model (no slides released nor videos taken)Wu (2013)
Topic not presentedDCM Item Discrimination and Computerized Adaptive TestingRupp, Templin, and Henson (2010): Chapter 13;
Cheng (2009);
Henson and Douglas (2005)
Topic not presentedExtensions of the LCDM: Generalized Models for Differing Data TypesBozard (2010);
Templin, Henson, Rupp, Jang,
and Ahmed (2008)
Skrondal and Rabe-Hesketh (2004), Ch. 2 and Ch. 4
Topic not presentedExtensions of the LCDM:
Bifactor and Testlet DCMs
Bradshaw and Templin (in press);
Choi (2010);
Others TBA

References (click on link for web link to paper)

Bozard, J. L. (2010). Invariance testing in diagnostic classification models. Unpublished masters’ thesis. The University of Georgia, Athens, GA.

Bradshaw, L., Izsák, A., Templin, J., & Jacobson, E. (2014). Diagnosing teachers’ understandings of rational numbers: Building a multidimensional test within the diagnostic classification framework. Educational measurement: Issues and practice33, 2-14.

Bradshaw, L. P., & Templin, J. (2014). Combining scaling and classification: A psychometric model for scaling ability and diagnosing misconceptions. Psychometrika, 79, 347-354.

Cai, L., Maydeu‐Olivares, A., Coffman, D. L., & Thissen, D. (2006). Limited‐information goodness‐of‐fit testing of item response theory models for sparse 2P tables. British Journal of Mathematical and Statistical Psychology59, 173-194.

Cheng, Y. (2009). When cognitive diagnosis meets computerized adaptive testing: CD-CAT.  Psychometrika74, 619-632.

Choi, H. J. (2010). A model that combines diagnostic classification assessment with mixture item response theory models Unpublished doctoral dissertation, University of Georgia, Athens, GA.

de la Torre, J. (2009). DINA model and parameter estimation: A didactic. Journal of Educational and Behavioral Statistics34, 115-130.

de la Torre, J. (2011). The generalized DINA model framework. Psychometrika,76, 179-199.

de la Torre, J., & Douglas, J. A. (2004). Higher-order latent trait models for cognitive diagnosis. Psychometrika69, 333-353.

Gorin, J. S. (2007). Test construction and diagnostic testing. In J. Leighton & M. J. Gierl (Eds.), Cognitively diagnostic assessment for education: Theory and applications (pp. 173-201). Cambridge, UK: Cambridge University Press.

Henson, R., & Douglas, J. (2005). Test construction for cognitive diagnosis. Applied Psychological Measurement29, 262-277.

Henson, R., Templin, J., & Willse, J. (2009). Defining a family of cognitive diagnosis models using log-linear models with latent variables. Psychometrika, 74, 191-210.

Jurich, D. P., & Bradshaw, L. P. (2014). An illustration of diagnostic classification modeling in student learning outcomes assessment. International Journal of Testing, 14, 49-72.

Maydeu-Olivares, A., & Joe, H. (2005). Limited-and full-information estimation and goodness-of-fit testing in 2 n contingency tables: a unified framework. Journal of the American Statistical Association100, 1009-1020.

Maydeu-Olivares, A., & Joe, H. (2014). Assessing approximate fit in categorical data analysis. Multivariate Behavioral Research, 49, 305-328.

Rupp, A. A., Templin, J., & Henson, R. A. (2010). Diagnostic measurement: Theory, methods, and applications. New York: Guilford Press.

Skrondal, A., & Rabe-Hesketh, S. (2004). Generalized latent variable modeling: Multilevel, longitudinal, and structural equation models. New York: Chapman & Hall / CRC.

Templin, J., & Bradshaw, L. (2013). Measuring the reliability of diagnostic classification model examinee estimates. Journal of Classification, 30, 251-275.

Templin, J., & Bradshaw, L. (2014a). Hierarchical diagnostic classification models: a family of models for estimating and testing attribute hierarchies. Psychometrika79, 317-339.

Templin, J., & Bradshaw, L. (2014). The use and misuse of psychometric models. Psychometrika, 79, 347-354.

Templin, J., Bradshaw, L., & Paek, P. (in press). A comprehensive framework for integrating innovative psychometric methodology into educational research. In A. Izsák, J. T. Remmillard, & J. Templin (Eds.), Psychometric methods in mathematics education: Opportunities, challenges, and interdisciplinary collaborations. Journal for Research in Mathematics Education monograph series. Reston, VA: National Council of Teachers of Mathematics.

Templin, J., & Henson, R. A. (2006). Measurement of psychological disorders using cognitive diagnosis models. Psychological Methods, 11, 287-305.

Templin, J., & Hoffman, L. (2013) Obtaining diagnostic classification model estimates using Mplus. Educational Measurement: Issues and Practice, 32(2), p. 37-50.

Templin, J., Henson, R., Rupp, A., Jang, E., & Ahmed, M. (2008). Cognitive diagnosis models for nominal response data. Paper presentation at the annual meeting of the National Council on Measurement in Education Society, New York, NY.

Templin, J. L., Henson, R. A., Templin, S. E., & Roussos, L. (2008).  Robustness of hierarchical modeling of skill association in cognitive diagnosis models.Applied Psychological Measurement, 32, 552-574.

von Davier, M. (2008). A general diagnostic model applied to language testing data. British Journal of Mathematical and Statistical Psychology, 61, 287-307.

von Davier, M., & Haberman, S. J. (2014). Hierarchical diagnostic classification models morphing into unidimensional ‘diagnostic’ classification models—a commentary. Psychometrika79, 340-346.

Wu, H. (2013). A comparison of general diagnostic models (GDM) and Bayesian networks using a middle school mathematics test. Unpublished doctoral dissertation, Florida State University, Tallahassee, FL.