Journal of Classification

, Volume 26, Issue 3, pp 329–360 | Cite as

Unfolding Incomplete Data: Guidelines for Unfolding Row-Conditional Rank Order Data with Random Missings

  • Frank M. T. A. Busing
  • Mark de Rooij


Unfolding creates configurations from preference information. In this paper, it is argued that not all preference information needs to be collected and that good solutions are still obtained, even when more than half of the data is missing. Simulation studies are conducted to compare missing data treatments, sources of missing data, and designs for the specification of missing data. Guidelines are provided and used in actual practice.


Unfolding Incomplete data Missing data BIBD PREFSCAL 


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of PsychologyLeiden UniversityLeidenthe Netherlands

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