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2012 | OriginalPaper | Chapter

8. Maximum Likelihood Conjoint Measurement

Authors : Kenneth Knoblauch, Laurence T. Maloney

Published in: Modeling Psychophysical Data in R

Publisher: Springer New York

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Abstract

Conjoint measurement allows the experimenter to estimate psychophysical scales that capture how two or more physical dimensions contribute to a perceptual judgment. It is most easily explained by an example. Figure 8.1 shows a range of stimuli taken from a study by Ho et al. [80]. Each stimulus was the image of an irregular surface (the original stimuli were rendered for binocular viewing at a higher resolution than those shown in the figure). The experimenters were interested in how the perceived roughness (which they refer to as “bumpiness) and glossiness of a surface were affected by variations in two physical parameters that plausibly affect perceived roughness and glossiness. They reported two experiments that differed only in the judgments observers made. In the first, observers judged perceived roughness, in the second, perceived glossiness.

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previous chapter Maximum Likelihood Difference Scaling
next chapter Mixed-Effects Models
Footnotes
1
See the example in [178] on p. 445.
 
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Metadata
Title
Maximum Likelihood Conjoint Measurement
Authors
Kenneth Knoblauch
Laurence T. Maloney
Copyright Year
2012
Publisher
Springer New York
Book
Modeling Psychophysical Data in R

Print ISBN: 978-1-4614-4474-9

Electronic ISBN: 978-1-4614-4475-6

Copyright Year: 2012

DOI
https://doi.org/10.1007/978-1-4614-4475-6_8

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