The Versatility of SpAM: A Fast, Efficient, Spatial Method of Data Collection for Multidimensional Scaling
Identifieur interne : 001905 ( Pmc/Curation ); précédent : 001904; suivant : 001906The Versatility of SpAM: A Fast, Efficient, Spatial Method of Data Collection for Multidimensional Scaling
Auteurs : Michael C. Hout ; Stephen D. Goldinger ; Ryan W. FergusonSource :
- Journal of experimental psychology. General [ 0096-3445 ] ; 2012.
Abstract
Although traditional methods to collect similarity data (for multidimensional scaling, MDS) are robust, they share a key shortcoming. Specifically, the possible pairwise comparisons in any set of objects grow rapidly as a function of set size. This leads to lengthy experimental protocols, or procedures that involve scaling stimulus subsets. We review existing methods of collecting similarity data, and critically examine a
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DOI: 10.1037/a0028860
PubMed: 22746700
PubMed Central: 3465534
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<author><name sortKey="Hout, Michael C" sort="Hout, Michael C" uniqKey="Hout M" first="Michael C." last="Hout">Michael C. Hout</name>
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<author><name sortKey="Goldinger, Stephen D" sort="Goldinger, Stephen D" uniqKey="Goldinger S" first="Stephen D." last="Goldinger">Stephen D. Goldinger</name>
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<author><name sortKey="Ferguson, Ryan W" sort="Ferguson, Ryan W" uniqKey="Ferguson R" first="Ryan W." last="Ferguson">Ryan W. Ferguson</name>
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<author><name sortKey="Ferguson, Ryan W" sort="Ferguson, Ryan W" uniqKey="Ferguson R" first="Ryan W." last="Ferguson">Ryan W. Ferguson</name>
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<series><title level="j">Journal of experimental psychology. General</title>
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<front><div type="abstract" xml:lang="en"><p id="P1">Although traditional methods to collect similarity data (for multidimensional scaling, MDS) are robust, they share a key shortcoming. Specifically, the possible pairwise comparisons in any set of objects grow rapidly as a function of set size. This leads to lengthy experimental protocols, or procedures that involve scaling stimulus subsets. We review existing methods of collecting similarity data, and critically examine a <italic>spatial arrangement method</italic>
(SpAM) proposed by <xref rid="R44" ref-type="bibr">Goldstone (1994a)</xref>
, in which similarity ratings are obtained by presenting many stimuli at once. The participant moves stimuli around the computer screen, placing them at distances from one another that are proportional to subjective similarity. This provides a fast, efficient, and user-friendly method for obtaining MDS spaces. Participants gave similarity ratings to artificially constructed visual stimuli (comprising 2–3 perceptual dimensions), and non-visual stimuli (animal names) with less-defined underlying dimensions. Ratings were obtained using four methods: pairwise comparisons, spatial arrangement, and two novel hybrid methods. We compared solutions from alternative methods to the pairwise method, finding that the SpAM produces high-quality MDS solutions. Monte Carlo simulations on degraded data suggest that the method is also robust to reductions in sample sizes and granularity. Moreover, coordinates derived from SpAM solutions accurately predicted discrimination among objects in “same/different” classification. In the General Discussion, we address the benefits of using a spatial medium to collect similarity measures.</p>
</div>
</front>
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<pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<pmc-dir>properties manuscript</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-journal-id">7502587</journal-id>
<journal-id journal-id-type="pubmed-jr-id">4729</journal-id>
<journal-id journal-id-type="nlm-ta">J Exp Psychol Gen</journal-id>
<journal-id journal-id-type="iso-abbrev">J Exp Psychol Gen</journal-id>
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<article-id pub-id-type="doi">10.1037/a0028860</article-id>
<article-id pub-id-type="manuscript">NIHMS379345</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Article</subject>
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<title-group><article-title>The Versatility of SpAM: A Fast, Efficient, Spatial Method of Data Collection for Multidimensional Scaling</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Hout</surname>
<given-names>Michael C.</given-names>
</name>
</contrib>
<contrib contrib-type="author"><name><surname>Goldinger</surname>
<given-names>Stephen D.</given-names>
</name>
</contrib>
<contrib contrib-type="author"><name><surname>Ferguson</surname>
<given-names>Ryan W.</given-names>
</name>
</contrib>
<aff id="A1">Arizona State University</aff>
</contrib-group>
<author-notes><corresp id="FN1">Please address correspondence to Michael C. Hout or Stephen D. Goldinger, Department of Psychology, Box 871104, Arizona State University, Tempe, AZ, 85287-1104., <email>Michael.Hout@asu.edu</email>
or <email>Goldinger@asu.edu</email>
</corresp>
</author-notes>
<pub-date pub-type="nihms-submitted"><day>23</day>
<month>5</month>
<year>2012</year>
</pub-date>
<pub-date pub-type="epub"><day>02</day>
<month>7</month>
<year>2012</year>
</pub-date>
<pub-date pub-type="ppub"><month>2</month>
<year>2013</year>
</pub-date>
<pub-date pub-type="pmc-release"><day>01</day>
<month>2</month>
<year>2014</year>
</pub-date>
<volume>142</volume>
<issue>1</issue>
<fpage>256</fpage>
<lpage>281</lpage>
<abstract><p id="P1">Although traditional methods to collect similarity data (for multidimensional scaling, MDS) are robust, they share a key shortcoming. Specifically, the possible pairwise comparisons in any set of objects grow rapidly as a function of set size. This leads to lengthy experimental protocols, or procedures that involve scaling stimulus subsets. We review existing methods of collecting similarity data, and critically examine a <italic>spatial arrangement method</italic>
(SpAM) proposed by <xref rid="R44" ref-type="bibr">Goldstone (1994a)</xref>
, in which similarity ratings are obtained by presenting many stimuli at once. The participant moves stimuli around the computer screen, placing them at distances from one another that are proportional to subjective similarity. This provides a fast, efficient, and user-friendly method for obtaining MDS spaces. Participants gave similarity ratings to artificially constructed visual stimuli (comprising 2–3 perceptual dimensions), and non-visual stimuli (animal names) with less-defined underlying dimensions. Ratings were obtained using four methods: pairwise comparisons, spatial arrangement, and two novel hybrid methods. We compared solutions from alternative methods to the pairwise method, finding that the SpAM produces high-quality MDS solutions. Monte Carlo simulations on degraded data suggest that the method is also robust to reductions in sample sizes and granularity. Moreover, coordinates derived from SpAM solutions accurately predicted discrimination among objects in “same/different” classification. In the General Discussion, we address the benefits of using a spatial medium to collect similarity measures.</p>
</abstract>
<funding-group><award-group><funding-source country="United States">National Institute on Deafness and Other Communication Disorders : NIDCD</funding-source>
<award-id>R01 DC004535 || DC</award-id>
</award-group>
</funding-group>
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</front>
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