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Unfolding incomplete data: guidelines for unfolding row-conditional rank order data with random missings. (English) Zbl 1337.62126

Summary: 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.

MSC:

62H30 Classification and discrimination; cluster analysis (statistical aspects)
62-07 Data analysis (statistics) (MSC2010)

Software:

SPSS; PROXSCAL
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Full Text: DOI

References:

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