Abstract
Judging goodness of fit in multidimensional scaling requires a comprehensive set of diagnostic tools instead of relying on stress rules of thumb. This article elaborates on corresponding strategies and gives practical guidelines for researchers to obtain a clear picture of the goodness of fit of a solution. Special emphasis will be placed on the use of permutation tests. The second part of the article focuses on goodness-of-fit assessment of an important variant of multidimensional scaling called unfolding, which can be applied to a broad range of psychological data settings. Two real-life data sets are presented in order to walk the reader through the entire set of diagnostic measures, tests, and plots. R code is provided as supplementary information that makes the whole goodness-of-fit assessment workflow, as presented in this article, fully reproducible.
Original language | English |
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Pages (from-to) | 772 - 789 |
Journal | Multivariate Behavioral Research |
Volume | 51 |
Issue number | 6 |
DOIs | |
Publication status | Published - 2016 |
Austrian Classification of Fields of Science and Technology (ÖFOS)
- 101018 Statistics
- 501
- 509013 Social statistics
- 509