Statistical treatment of free sorting data by means of correspondence and cluster analyses
•New strategies for the analysis of free sorting data are discussed.•Correspondence and cluster analyses are applied on the co-occurrence matrices.•The relationships among the stimuli on the one hand and among the subjects on the other hand are investigated.•The stimuli are partitioned into homogene...
Gespeichert in:
Veröffentlicht in: | Food quality and preference 2018-09, Vol.68, p.1-11 |
---|---|
Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 11 |
---|---|
container_issue | |
container_start_page | 1 |
container_title | Food quality and preference |
container_volume | 68 |
creator | Cariou, V. Qannari, E.M. |
description | •New strategies for the analysis of free sorting data are discussed.•Correspondence and cluster analyses are applied on the co-occurrence matrices.•The relationships among the stimuli on the one hand and among the subjects on the other hand are investigated.•The stimuli are partitioned into homogeneous clusters.•The subjects are segmented into homogeneous groups.•The different methods of analyses complement each other and present a global coherence.
Several statistical procedures have been proposed for the analysis of the data from a free sorting task. A straightforward strategy of analysis based on correspondence analysis and cluster analysis performed on the co-occurrence matrix is proposed herein. More specifically, two situations are considered depending on whether the aim is to depict the relationships among the stimuli or to investigate the agreement among the subjects. The approach of analysis is illustrated on the basis of free sorting data characterizing chocolate products. |
doi_str_mv | 10.1016/j.foodqual.2018.01.011 |
format | Article |
fullrecord | <record><control><sourceid>hal_cross</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_hal_02626160v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0950329318300600</els_id><sourcerecordid>oai_HAL_hal_02626160v1</sourcerecordid><originalsourceid>FETCH-LOGICAL-c383t-cf23de962b7d025eef69c9f3fbd7e68b3b981b35052322388f20a560ee368e453</originalsourceid><addsrcrecordid>eNqFUMFKAzEUDKJgrf6C5Oph60vSTXdvlqJWKHhQL15CNnnRlO2mJmmhf-8uVa_CwHu8NzMwQ8g1gwkDJm_XExeC_drpdsKBVRNgPdgJGbFqJgoppuKUjKAuoRC8FufkIqU1AJsB4yPy_pJ19il7o1uaI-q8wS7T4KiLiDSFmH33Qa3OmjYHukHdpeFrQoyYtqGz2BmkurPUtLuUMfa7bg8J0yU5c7pNePUzx-Tt4f51sSxWz49Pi_mqMKISuTCOC4u15M3MAi8RnaxN7YRr7Axl1YimrlgjSii54FxUleOgSwmIQlY4LcWY3Bx9P3WrttFvdDyooL1azldquAGXXDIJe9Zz5ZFrYkgpovsTMFBDm2qtfttUQ5sKWI9BeHcUYp9k7zGqZPwQ3fqIJisb_H8W37WSgiA</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Statistical treatment of free sorting data by means of correspondence and cluster analyses</title><source>Elsevier ScienceDirect Journals</source><creator>Cariou, V. ; Qannari, E.M.</creator><creatorcontrib>Cariou, V. ; Qannari, E.M.</creatorcontrib><description>•New strategies for the analysis of free sorting data are discussed.•Correspondence and cluster analyses are applied on the co-occurrence matrices.•The relationships among the stimuli on the one hand and among the subjects on the other hand are investigated.•The stimuli are partitioned into homogeneous clusters.•The subjects are segmented into homogeneous groups.•The different methods of analyses complement each other and present a global coherence.
Several statistical procedures have been proposed for the analysis of the data from a free sorting task. A straightforward strategy of analysis based on correspondence analysis and cluster analysis performed on the co-occurrence matrix is proposed herein. More specifically, two situations are considered depending on whether the aim is to depict the relationships among the stimuli or to investigate the agreement among the subjects. The approach of analysis is illustrated on the basis of free sorting data characterizing chocolate products.</description><identifier>ISSN: 0950-3293</identifier><identifier>EISSN: 1873-6343</identifier><identifier>DOI: 10.1016/j.foodqual.2018.01.011</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>Chemical and Process Engineering ; Cluster analysis ; Co-occurrence matrix ; Correspondence analysis ; Engineering Sciences ; Food engineering ; Free sorting ; Life Sciences</subject><ispartof>Food quality and preference, 2018-09, Vol.68, p.1-11</ispartof><rights>2018 Elsevier Ltd</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c383t-cf23de962b7d025eef69c9f3fbd7e68b3b981b35052322388f20a560ee368e453</citedby><cites>FETCH-LOGICAL-c383t-cf23de962b7d025eef69c9f3fbd7e68b3b981b35052322388f20a560ee368e453</cites><orcidid>0000-0003-4091-5910</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0950329318300600$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,776,780,881,3536,27903,27904,65309</link.rule.ids><backlink>$$Uhttps://hal.inrae.fr/hal-02626160$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Cariou, V.</creatorcontrib><creatorcontrib>Qannari, E.M.</creatorcontrib><title>Statistical treatment of free sorting data by means of correspondence and cluster analyses</title><title>Food quality and preference</title><description>•New strategies for the analysis of free sorting data are discussed.•Correspondence and cluster analyses are applied on the co-occurrence matrices.•The relationships among the stimuli on the one hand and among the subjects on the other hand are investigated.•The stimuli are partitioned into homogeneous clusters.•The subjects are segmented into homogeneous groups.•The different methods of analyses complement each other and present a global coherence.
Several statistical procedures have been proposed for the analysis of the data from a free sorting task. A straightforward strategy of analysis based on correspondence analysis and cluster analysis performed on the co-occurrence matrix is proposed herein. More specifically, two situations are considered depending on whether the aim is to depict the relationships among the stimuli or to investigate the agreement among the subjects. The approach of analysis is illustrated on the basis of free sorting data characterizing chocolate products.</description><subject>Chemical and Process Engineering</subject><subject>Cluster analysis</subject><subject>Co-occurrence matrix</subject><subject>Correspondence analysis</subject><subject>Engineering Sciences</subject><subject>Food engineering</subject><subject>Free sorting</subject><subject>Life Sciences</subject><issn>0950-3293</issn><issn>1873-6343</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNqFUMFKAzEUDKJgrf6C5Oph60vSTXdvlqJWKHhQL15CNnnRlO2mJmmhf-8uVa_CwHu8NzMwQ8g1gwkDJm_XExeC_drpdsKBVRNgPdgJGbFqJgoppuKUjKAuoRC8FufkIqU1AJsB4yPy_pJ19il7o1uaI-q8wS7T4KiLiDSFmH33Qa3OmjYHukHdpeFrQoyYtqGz2BmkurPUtLuUMfa7bg8J0yU5c7pNePUzx-Tt4f51sSxWz49Pi_mqMKISuTCOC4u15M3MAi8RnaxN7YRr7Axl1YimrlgjSii54FxUleOgSwmIQlY4LcWY3Bx9P3WrttFvdDyooL1azldquAGXXDIJe9Zz5ZFrYkgpovsTMFBDm2qtfttUQ5sKWI9BeHcUYp9k7zGqZPwQ3fqIJisb_H8W37WSgiA</recordid><startdate>20180901</startdate><enddate>20180901</enddate><creator>Cariou, V.</creator><creator>Qannari, E.M.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>AAYXX</scope><scope>CITATION</scope><scope>1XC</scope><orcidid>https://orcid.org/0000-0003-4091-5910</orcidid></search><sort><creationdate>20180901</creationdate><title>Statistical treatment of free sorting data by means of correspondence and cluster analyses</title><author>Cariou, V. ; Qannari, E.M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c383t-cf23de962b7d025eef69c9f3fbd7e68b3b981b35052322388f20a560ee368e453</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Chemical and Process Engineering</topic><topic>Cluster analysis</topic><topic>Co-occurrence matrix</topic><topic>Correspondence analysis</topic><topic>Engineering Sciences</topic><topic>Food engineering</topic><topic>Free sorting</topic><topic>Life Sciences</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cariou, V.</creatorcontrib><creatorcontrib>Qannari, E.M.</creatorcontrib><collection>CrossRef</collection><collection>Hyper Article en Ligne (HAL)</collection><jtitle>Food quality and preference</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cariou, V.</au><au>Qannari, E.M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Statistical treatment of free sorting data by means of correspondence and cluster analyses</atitle><jtitle>Food quality and preference</jtitle><date>2018-09-01</date><risdate>2018</risdate><volume>68</volume><spage>1</spage><epage>11</epage><pages>1-11</pages><issn>0950-3293</issn><eissn>1873-6343</eissn><abstract>•New strategies for the analysis of free sorting data are discussed.•Correspondence and cluster analyses are applied on the co-occurrence matrices.•The relationships among the stimuli on the one hand and among the subjects on the other hand are investigated.•The stimuli are partitioned into homogeneous clusters.•The subjects are segmented into homogeneous groups.•The different methods of analyses complement each other and present a global coherence.
Several statistical procedures have been proposed for the analysis of the data from a free sorting task. A straightforward strategy of analysis based on correspondence analysis and cluster analysis performed on the co-occurrence matrix is proposed herein. More specifically, two situations are considered depending on whether the aim is to depict the relationships among the stimuli or to investigate the agreement among the subjects. The approach of analysis is illustrated on the basis of free sorting data characterizing chocolate products.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.foodqual.2018.01.011</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0003-4091-5910</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0950-3293 |
ispartof | Food quality and preference, 2018-09, Vol.68, p.1-11 |
issn | 0950-3293 1873-6343 |
language | eng |
recordid | cdi_hal_primary_oai_HAL_hal_02626160v1 |
source | Elsevier ScienceDirect Journals |
subjects | Chemical and Process Engineering Cluster analysis Co-occurrence matrix Correspondence analysis Engineering Sciences Food engineering Free sorting Life Sciences |
title | Statistical treatment of free sorting data by means of correspondence and cluster analyses |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-25T13%3A38%3A19IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-hal_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Statistical%20treatment%20of%20free%20sorting%20data%20by%20means%20of%20correspondence%20and%20cluster%20analyses&rft.jtitle=Food%20quality%20and%20preference&rft.au=Cariou,%20V.&rft.date=2018-09-01&rft.volume=68&rft.spage=1&rft.epage=11&rft.pages=1-11&rft.issn=0950-3293&rft.eissn=1873-6343&rft_id=info:doi/10.1016/j.foodqual.2018.01.011&rft_dat=%3Chal_cross%3Eoai_HAL_hal_02626160v1%3C/hal_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_els_id=S0950329318300600&rfr_iscdi=true |