Dr Matthias von Davier

Dr. Matthias von Davier is a principal research scientist in the Research & Development Division at Educational Testing Service. He joined ETS, which is located in Princeton, NJ, USA, in 2000. He earned his Ph.D. in psychology from University of Kiel, Germany, in 1996, specializing in psychometrics.

At ETS, Dr. von Davier manages a group of researchers concerned with methodological questions arising in large-scale international comparative studies in education. He is one of the editors of the periodical “Issues and Methodologies in Large Scale Assessments,” which is jointly published the International Association for the Evaluation of Educational Achievement (IEA) and ETS through the IEA-ETS Research Institute (IERI). His current work at ETS involves the psychometric methodologies used in analysing cognitive skills data and background data from large-scale educational surveys, such as the Organisation for Economic Co-operation and Development’s upcoming PIAAC and the ongoing PISA, as well as IEA’s TIMSS and PIRLS. His work at ETS also involves the development of software for multidimensional models for item response data, and the improvement of models and estimation methods for the analysis of data from large-scale educational survey assessments.

Prior to joining ETS, Dr. von Davier led a research group on computer assisted science learning, was co-director of the “Computer as a tool for learning” section at the Institute for Science Education (IPN) in Kiel, Germany, and was an associate member of the Psychometrics & Methodology Department of IPN. During his 10-year tenure at IPN, he developed commercially available software for analyses with the Rasch model, with latent class analysis models, and with mixture distribution Rasch models. He taught courses on foundations of neural networks and on psychometrics and educational psychology at the University of Kiel for the Department of Psychology as well as for the Department of Education. He gave various invited workshops and mini-courses on psychometrics and recent developments in item response theory models. In 1997, he received a postdoctoral fellowship award from ETS and an additional research award from the German Science Foundation. From 1993 to 1997, and he was part of the research staff on the German Science Foundation funded project on “development and validation of psychometric mixture distribution models” at the University of Kiel.


Dr. von Davier’s research focuses on developing psychometric models for analyzing data from complex item and respondent samples and on integrating diagnostic procedures into these methods. His areas of expertise includes topics such as item response theory, latent class analysis, classification and mixture distribution models, diagnostic models, computational statistics, person-fit, item-fit, and model checking, as well as hierarchical extension of models for categorical data analysis, and the analytical methodologies used in large scale educational surveys.

Dr. von Davier’s applied research uses these methodologies to analyse data from educational testing, large scale survey assessments of student skills and adult literacy, to computer based assessment of skills, and to the analysis of questionnaire data.

Selected publications

  • von Davier, M. Sinharay, S., Oranje, A., & Beaton, A. (2006) Statistical procedures used in the National Assessment of Educational Progress (NAEP): Recent developments and future directions. In C. R. Rao and S. Sinharay (Eds.), Handbook of statistics (vol. 26): Psychometrics. Amsterdam: Elsevier.
  • von Davier, M., & Rost, J. (2006) Mixture distribution item response models. In C. R. Rao and S. Sinharay (Eds.), Handbook of statistics (vol. 26): Psychometrics. Amsterdam: Elsevier.
  • von Davier, M., & Yamamoto, K. (2007). Mixture distribution Rasch models and hybrid Rasch models. Chapter 6 in M. von Davier and C.H. Carstensen (Eds.), Multivariate and mixture distribution Rasch models. Springer: New York.
  • Mazzeo, J., & von Davier, M. (2008). Review of the Programme for International Student Assessment (PISA) Test Design: Recommendations for fostering stability in assessment results. Available at: doc.ref. EDU/PISA/GB(2008)28; Retrieved 12/12/2008 from http://www.oecd.org/dataoecd/44/49/41731967.pdf
  • von Davier, M. (2008). The mixture general diagnostic model. In G. R. Hancock and K. M. Samuelson (Eds.), Advances in latent variable mixture models. Information Age Publishing.
  • von Davier, M. (2008, November). A general diagnostic model applied to language testing data. British Journal of Mathematical and Statistical Psychology, 61(2), 287-307.
  • von Davier, M., DiBello, L., & Yamamoto, K. (2008) Reporting test outcomes using models for cognitive diagnosis. Chapter 7 in J. Hartig, E. Klieme, and D. Leutner (Eds.), Assessment of competencies in educational contexts (pp. 151-176). Hogrefe & Huber Publishers.
  • von Davier, M. (2009, March). Some notes on the reinvention of latent structure models as diagnostic classification models. Measurement – Interdisciplinary Research and Perspectives, 7(1), 67-74.
  • von Davier, M. (2009, March). Is there need for the 3PL IRT model? Guess what? Measurement – Interdisciplinary Research and Perspectives, 7(2), 110-114.
  • von Davier, M., Gonzalez, E., & Mislevy, R. (2009) What are plausible values and why are they useful? In M. von Davier and D. Hastedt (Eds.), IERI monograph series: Issues and methodologies in large scale assessments (vol. 2). IEA-ETS Research Institute.
  • von Davier, M. (2009). Mixture distribution item response theory, latent class analysis, and diagnostic mixture models. In S. Embretson (Ed.), Measuring psychological constructs: Advances in model-based approaches. APA Press (ISBN: 978-1-4338-0691-9), pp. 11-34.
  • Rutkowski, L., Gonzalez, E., Joncas, M., & von Davier, M. (2010, March). International large-scale assessment data: Issues in secondary analysis and reporting. Educational Researcher, 39(2), 142-151.
  • von Davier, M. (2010). Why sum scores may not tell us all about test takers. In L. Wang (Ed.), Special issue on quantitative research methodology, Newborn and Infant Nursing Reviews 10(1), 27-36.
  • von Davier, M., & Sinharay, S. (2010). Stochastic approximation for latent regression item response models. Journal of Educational and Behavioral Statistics, 35(2), 174-193.
  • Rose, N., von Davier, M., & Xu, X. (2010). Modeling non-ignorable missing data with IRT (ETS Research Report no. RR-10-10). Princeton, N.J.: ETS.
  • von Davier, M.  (2010). Hierarchical mixtures of diagnostic models. Psychological Test and Assessment Modeling, 52(1), 8-28. Retrieved May 10, 2010, from: http://www.psychologie-aktuell.com/fileadmin/download/ptam/1-2010/02_vonDavier.pdf
  • Haberman, S. J., von Davier, M., & Lee, Y. (expected 2011). Comparison of multidimensional item response models: Multivariate normal ability distributions versus multivariate polytomous ability distributions. In G. Hancock, and G. Macready (Eds.), Advances in latent class modeling – Festschrift for C. Dayton. University of Maryland: College Park.
  • von Davier, M., Xu, X., & Carstensen, C. H. (accepted for publication). Using the general diagnostic model for measuring growth in a longitudinal large scale assessment. Psychometrika.
vondavier profile


  • Department associate


  • Senior Research Fellow

Research groups

  • SELF