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Applied Psychological Measurement >
Volume 11, 1987 >
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| Title: | A stochastic three-way unfolding model for asymmetric binary data |
| Authors: | DeSarbo, Wayne S.
Lehmann, Donald R.
Holbrook, Morris B.
Havlena, William J.
Gupta, Sunil |
| Issue Date: | 1987 |
| Citation: | DeSarbo, Wayne S, Lehmann, Donald R, Holbrook, Morris B, Havlena, William J & et al. (1987). A stochastic three-way unfolding model for asymmetric binary data. Applied Psychological Measurement, 11, 397-418. doi:10.1177/014662168701100406 |
| Abstract: | This paper presents a new stochastic three-way unfolding
method designed to analyze asymmetric three-way,
two-mode binary data. As in the metric three-way
unfolding models presented by DeSarbo (1978)
and by DeSarbo and Carroll (1980, 1981, 1985), this
procedure estimates a joint space of row and column
objects, as well as weights reflecting the third way of
the array, such as individual differences. Unlike the
traditional metric three-way unfolding model, this new
methodology is based on stochastic assumptions using
an underlying threshold model, generalizing the work
of DeSarbo and Hoffman (1986) to three-way and
asymmetric binary data. The literature concerning the
spatial treatment of such binary data is reviewed. The
nonlinear probit-like model is described, as well as the
maximum likelihood algorithm used to estimate its
parameter values. Results of a monte carlo study applying
this new method to synthetic datasets are presented.
The new method was also applied to real data
from a study concerning word (emotion) associations
in consumer behavior. Possibilities for future research
and applications are discussed. |
| Permanent URL: | http://purl.umn.edu/104074 |
| Appears in Collections: | Volume 11, 1987
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