Hans Friedrich Koehn

Research:

(1) Machine Learning / Scaling, Clustering and Classification

(2) Cognitive Diagnosis / Q-Matrix Theory

(3) Combinatorial data analysis of individual differences based on multiple proximity matrices

Selected Publications:

Kim, H., Köhn, H. F., & Chiu, C.-Y. (in press). On identifiability conditions in cognitive diagnosis and their implications for Q-Matrix estimation. British Journal of Mathematical and Statistical Psychology.

Kwon, S., Zhang, S., Köhn, H. F., & Zhang, B.  (2025).  MCMC stopping rules in latent variable modeling.  British Journal of Mathematical and Statistical Psychology, 78(1), 225–257.

Wang, Y., Chiu, C. Y., & Köhn, H. F. (2025).  Nonparametric CD-CAT for multiple-choice items: Item selection method and Q-optimality.  British Journal of Mathematical and Statistical Psychology, 78(1), 61–83.

Köhn, H. F., Chiu, C.-Y. , Oluwalana, O. O., Kim, H., & Wang, Y. (2025). A Two-Step Q-Matrix Estimation Method. Applied Psychological Measurement, 49, 3–28.

Chiu, C.-Y., Köhn, H. F., & Ma, W. (2023).  Commentary on “Extending the basic local independence model to polytomous data” by Stefanutti, de Chiusole, Anselmi, and Spoto. Psychometrika, 88(2), 656–671.

Köhn, H. F., & Chiu, C.-Y. (2021).  A unified theory of the completeness of Q-matrices for the DINA model.  Journal of Classification, 38, 500–518.

Chiu, C.-Y., & Köhn, H. F. (2019). Consistency theory for the General NonParametric Classification Method. Psychometrika, 84, 830–845.

Köhn, H. F., & Chiu, C.-Y. (2019).  Attribute hierarchy models in cognitive diagnosis: Identifiability of the latent attribute space and conditions for completeness of the Q-matrix.    Journal of Classification, 36, 541–565.

Köhn, H. F., & Chiu, C.-Y. (2017). A procedure for assessing the completeness of the Q-matrices of cognitively diagnostic tests. Psychometrika, 82, 112–132.

Chiu, C.-Y., & Köhn, H. F. (2016). The Reduced RUM as a logit model: Parameterization and constraints.  Psychometrika, 81, 350–370.

Köhn, H. F. (2011). A review of multiobjective programming and its application in quantitative psychology.  Journal of Mathematical Psychology, 55, 386–396.

Köhn, H. F., Steinley, D., & Brusco, M. J. (2010). The p-median model as a tool for clustering psychological data.  Psychological Methods, 15, 87–95.