Research Output per year

## Personal profile

### Research Interests

My current research concerns three lines of work:

(1) Combinatorial data analysis of individual differences based on multiple proximity matrices observed from different data sources (e.g., subjects, experimental conditions, time points);

(2) Large-scale nonmodel-based clustering, with particular focus on the *p*-median model;

(3) Cognitively Diagnostic Modeling

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**Selected Publications:**

Chiu, C.-Y., &** Köhn, H. F. **(in press). Consistency theory for the General NonParametric Classification Method.

*Psychometrika.*

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

**Köhn**, H. F., & Chiu, C.-Y. (2018). How to build a complete Q-matrix for a cognitively diagnostic test. *Journal of Classification, 35*, 273–299.

**Köhn**, H. F. (2017). Citation classics commentary on Greenhouse and Geisser (1959): On methods in the analysis of profile data. *Psychometrika, 82*, 1209–1211.

**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.

**Köhn**, H. F., & Chiu, C.-Y. (2016). A proof of the duality of the DINA model and the DINO model. *Journal of Classification, 33*, 171-184.

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

Chiu, C.-Y., & **Köhn**, H. F. (2016). Consistency of cluster analysis for cognitive diagnosis: The Reduced Reparameterized Unified Model and the General Diagnostic Model. *Psychometrika, 81*, 585-610.

**Köhn**, H. F., & Hubert, L. J. (2015). Hierarchical cluster analysis. Wiley StatsRef: Statistics Reference Online (WSR).

**Köhn**, H. F., Chiu, C.-Y., & Brusco, M. J. (2015). Heuristic cognitive diagnosis when the Q-matrix is unknown. *British Journal of Mathematical and Statistical Psychology, 68*, 268-291.

**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. (2010). Representation of individual differences in rectangular proximity data through anti-Q matrix decomposition. *Computational Statistics and Data Analysis, 54*, 2343-2357.

**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.

Brusco, M. J., & **Köhn**, H. F. (2009). Clustering qualitative data based on binary equivalence relations: a variable neighborhood search procedure for the clique partitioning problem. *Psychometrika, 74*, 685-703.

Brusco, M. J., & **Köhn**, H. F. (2009). Exemplar-based clustering via simulated annealing: a comparison to affinity propagation and vertex substitution. *Psychometrika, 74*, 457-475.

Brusco, M. J., & **Köhn**, H. F. (2008). Optimal partitioning of a data set based on the p-median model. *Psychometrika, 73*, 89-105.

Brusco, M. J., & **Köhn**, H. F. (2008). Comment on “Clustering by passing messages between data points”. *Science, 319*, 726c.

Brusco, M. J., **Köhn**, H. F., & Stahl, S. (2008). Heuristic implementation of dynamic programming for matrix permutation problems in combinatorial data analysis. *Psychometrika, 73*, 503-522.

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## Research Output 2006 2019

## Additive Trees for Fitting Three-Way (Multiple Source) Proximity Data

Koehn, H. F. & Kern, J. L., Jan 1 2019,*Quantitative Psychology - 83rd Annual Meeting of the Psychometric Society, 2018.*Wiberg, M., Culpepper, S., Janssen, R., González, J. & Molenaar, D. (eds.). Springer New York LLC, p. 403-413 11 p. (Springer Proceedings in Mathematics and Statistics; vol. 265).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

## Consistency Theory for the General Nonparametric Classification Method

Chiu, C. Y. & Koehn, H. F., Sep 15 2019, In : Psychometrika. 84, 3, p. 830-845 16 p.Research output: Contribution to journal › Article

## Residual analysis for unidimensional scaling in the L_{2}-norm

Brusco, M. J., Steinley, D. & Koehn, H. F., Aug 9 2019, In : Communications in Statistics: Simulation and Computation. 48, 7, p. 2210-2221 12 p.Research output: Contribution to journal › Article

## Attribute Hierarchy Models in Cognitive Diagnosis: Identifiability of the Latent Attribute Space and Conditions for Completeness of the Q-Matrix

Koehn, H. F. & Chiu, C. Y., Jan 1 2018, (Accepted/In press) In : Journal of Classification.Research output: Contribution to journal › Article

## How to Build a Complete Q-Matrix for a Cognitively Diagnostic Test

Koehn, H. F. & Chiu, C. Y., Jul 1 2018, In : Journal of Classification. 35, 2, p. 273-299 27 p.Research output: Contribution to journal › Article