Model comparison in ANOVA
Analysis of variance (ANOVA), the workhorse analysis of experimental designs, consists of F -tests of main effects and interactions. Yet, testing, including traditional ANOVA, has been recently critiqued on a number of theoretical and practical grounds. In light of these critiques, model comparison...
Gespeichert in:
| Veröffentlicht in: | Psychonomic bulletin & review 2016-12, Vol.23 (6), p.1779-1786 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 1786 |
|---|---|
| container_issue | 6 |
| container_start_page | 1779 |
| container_title | Psychonomic bulletin & review |
| container_volume | 23 |
| creator | Rouder, Jeffrey N. Engelhardt, Christopher R. McCabe, Simon Morey, Richard D. |
| description | Analysis of variance (ANOVA), the workhorse analysis of experimental designs, consists of
F
-tests of main effects and interactions. Yet, testing, including traditional ANOVA, has been recently critiqued on a number of theoretical and practical grounds. In light of these critiques, model comparison and model selection serve as an attractive alternative. Model comparison differs from testing in that one can support a null or nested model vis-a-vis a more general alternative by penalizing more flexible models. We argue this ability to support more simple models allows for more nuanced theoretical conclusions than provided by traditional ANOVA
F
-tests. We provide a model comparison strategy and show how ANOVA models may be reparameterized to better address substantive questions in data analysis. |
| doi_str_mv | 10.3758/s13423-016-1026-5 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1826667695</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1826667695</sourcerecordid><originalsourceid>FETCH-LOGICAL-c415t-d2be3db7642135b154d931dd5c0b22464867316bd1da9c1058cf7568d82e199c3</originalsourceid><addsrcrecordid>eNp1kE1LAzEQhoMotlZ_QC9S8OIlmsnXJsdS_AK1F_UadpNUtuxuatI9-O9N2SoieJqBeead4UFoCuSKFUJdJ2CcMkxAYiBUYnGAxiAYYMEoOcw9kRprpvgInaS0JoQIqeUxGtGCSCU4G6PpU3C-mdnQbspYp9DN6m42f16-zU_R0apskj_b1wl6vb15Wdzjx-Xdw2L-iC0HscWOVp65qpCcAhMVCO40A-eEJRWlXHIlCwaycuBKbYEIZVeFkMop6kFryybocsjdxPDR-7Q1bZ2sb5qy86FPBhSVUhZSi4xe_EHXoY9d_i5TXBHNCq4yBQNlY0gp-pXZxLot46cBYnbezODNZG9m583sks_3yX3Vevez8S0qA3QAUh517z7-Ov1v6hf8h3PU</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1848093748</pqid></control><display><type>article</type><title>Model comparison in ANOVA</title><source>MEDLINE</source><source>SpringerLink Journals</source><source>EZB-FREE-00999 freely available EZB journals</source><creator>Rouder, Jeffrey N. ; Engelhardt, Christopher R. ; McCabe, Simon ; Morey, Richard D.</creator><creatorcontrib>Rouder, Jeffrey N. ; Engelhardt, Christopher R. ; McCabe, Simon ; Morey, Richard D.</creatorcontrib><description>Analysis of variance (ANOVA), the workhorse analysis of experimental designs, consists of
F
-tests of main effects and interactions. Yet, testing, including traditional ANOVA, has been recently critiqued on a number of theoretical and practical grounds. In light of these critiques, model comparison and model selection serve as an attractive alternative. Model comparison differs from testing in that one can support a null or nested model vis-a-vis a more general alternative by penalizing more flexible models. We argue this ability to support more simple models allows for more nuanced theoretical conclusions than provided by traditional ANOVA
F
-tests. We provide a model comparison strategy and show how ANOVA models may be reparameterized to better address substantive questions in data analysis.</description><identifier>ISSN: 1069-9384</identifier><identifier>EISSN: 1531-5320</identifier><identifier>DOI: 10.3758/s13423-016-1026-5</identifier><identifier>PMID: 27068543</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Analysis of Variance ; Asymmetry ; Behavioral Science and Psychology ; Biomedical Research ; Brief Report ; Cognitive Psychology ; Experimental psychology ; Flexibility ; Humans ; Models, Statistical ; Noise ; Psychologists ; Psychology ; Variance analysis</subject><ispartof>Psychonomic bulletin & review, 2016-12, Vol.23 (6), p.1779-1786</ispartof><rights>Psychonomic Society, Inc. 2016</rights><rights>Copyright Springer Science & Business Media Dec 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c415t-d2be3db7642135b154d931dd5c0b22464867316bd1da9c1058cf7568d82e199c3</citedby><cites>FETCH-LOGICAL-c415t-d2be3db7642135b154d931dd5c0b22464867316bd1da9c1058cf7568d82e199c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.3758/s13423-016-1026-5$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.3758/s13423-016-1026-5$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27068543$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Rouder, Jeffrey N.</creatorcontrib><creatorcontrib>Engelhardt, Christopher R.</creatorcontrib><creatorcontrib>McCabe, Simon</creatorcontrib><creatorcontrib>Morey, Richard D.</creatorcontrib><title>Model comparison in ANOVA</title><title>Psychonomic bulletin & review</title><addtitle>Psychon Bull Rev</addtitle><addtitle>Psychon Bull Rev</addtitle><description>Analysis of variance (ANOVA), the workhorse analysis of experimental designs, consists of
F
-tests of main effects and interactions. Yet, testing, including traditional ANOVA, has been recently critiqued on a number of theoretical and practical grounds. In light of these critiques, model comparison and model selection serve as an attractive alternative. Model comparison differs from testing in that one can support a null or nested model vis-a-vis a more general alternative by penalizing more flexible models. We argue this ability to support more simple models allows for more nuanced theoretical conclusions than provided by traditional ANOVA
F
-tests. We provide a model comparison strategy and show how ANOVA models may be reparameterized to better address substantive questions in data analysis.</description><subject>Analysis of Variance</subject><subject>Asymmetry</subject><subject>Behavioral Science and Psychology</subject><subject>Biomedical Research</subject><subject>Brief Report</subject><subject>Cognitive Psychology</subject><subject>Experimental psychology</subject><subject>Flexibility</subject><subject>Humans</subject><subject>Models, Statistical</subject><subject>Noise</subject><subject>Psychologists</subject><subject>Psychology</subject><subject>Variance analysis</subject><issn>1069-9384</issn><issn>1531-5320</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp1kE1LAzEQhoMotlZ_QC9S8OIlmsnXJsdS_AK1F_UadpNUtuxuatI9-O9N2SoieJqBeead4UFoCuSKFUJdJ2CcMkxAYiBUYnGAxiAYYMEoOcw9kRprpvgInaS0JoQIqeUxGtGCSCU4G6PpU3C-mdnQbspYp9DN6m42f16-zU_R0apskj_b1wl6vb15Wdzjx-Xdw2L-iC0HscWOVp65qpCcAhMVCO40A-eEJRWlXHIlCwaycuBKbYEIZVeFkMop6kFryybocsjdxPDR-7Q1bZ2sb5qy86FPBhSVUhZSi4xe_EHXoY9d_i5TXBHNCq4yBQNlY0gp-pXZxLot46cBYnbezODNZG9m583sks_3yX3Vevez8S0qA3QAUh517z7-Ov1v6hf8h3PU</recordid><startdate>20161201</startdate><enddate>20161201</enddate><creator>Rouder, Jeffrey N.</creator><creator>Engelhardt, Christopher R.</creator><creator>McCabe, Simon</creator><creator>Morey, Richard D.</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>4T-</scope><scope>4U-</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope></search><sort><creationdate>20161201</creationdate><title>Model comparison in ANOVA</title><author>Rouder, Jeffrey N. ; Engelhardt, Christopher R. ; McCabe, Simon ; Morey, Richard D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c415t-d2be3db7642135b154d931dd5c0b22464867316bd1da9c1058cf7568d82e199c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Analysis of Variance</topic><topic>Asymmetry</topic><topic>Behavioral Science and Psychology</topic><topic>Biomedical Research</topic><topic>Brief Report</topic><topic>Cognitive Psychology</topic><topic>Experimental psychology</topic><topic>Flexibility</topic><topic>Humans</topic><topic>Models, Statistical</topic><topic>Noise</topic><topic>Psychologists</topic><topic>Psychology</topic><topic>Variance analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rouder, Jeffrey N.</creatorcontrib><creatorcontrib>Engelhardt, Christopher R.</creatorcontrib><creatorcontrib>McCabe, Simon</creatorcontrib><creatorcontrib>Morey, Richard D.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Docstoc</collection><collection>University Readers</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest Psychology</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Psychonomic bulletin & review</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rouder, Jeffrey N.</au><au>Engelhardt, Christopher R.</au><au>McCabe, Simon</au><au>Morey, Richard D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Model comparison in ANOVA</atitle><jtitle>Psychonomic bulletin & review</jtitle><stitle>Psychon Bull Rev</stitle><addtitle>Psychon Bull Rev</addtitle><date>2016-12-01</date><risdate>2016</risdate><volume>23</volume><issue>6</issue><spage>1779</spage><epage>1786</epage><pages>1779-1786</pages><issn>1069-9384</issn><eissn>1531-5320</eissn><abstract>Analysis of variance (ANOVA), the workhorse analysis of experimental designs, consists of
F
-tests of main effects and interactions. Yet, testing, including traditional ANOVA, has been recently critiqued on a number of theoretical and practical grounds. In light of these critiques, model comparison and model selection serve as an attractive alternative. Model comparison differs from testing in that one can support a null or nested model vis-a-vis a more general alternative by penalizing more flexible models. We argue this ability to support more simple models allows for more nuanced theoretical conclusions than provided by traditional ANOVA
F
-tests. We provide a model comparison strategy and show how ANOVA models may be reparameterized to better address substantive questions in data analysis.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>27068543</pmid><doi>10.3758/s13423-016-1026-5</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1069-9384 |
| ispartof | Psychonomic bulletin & review, 2016-12, Vol.23 (6), p.1779-1786 |
| issn | 1069-9384 1531-5320 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1826667695 |
| source | MEDLINE; SpringerLink Journals; EZB-FREE-00999 freely available EZB journals |
| subjects | Analysis of Variance Asymmetry Behavioral Science and Psychology Biomedical Research Brief Report Cognitive Psychology Experimental psychology Flexibility Humans Models, Statistical Noise Psychologists Psychology Variance analysis |
| title | Model comparison in ANOVA |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-29T03%3A02%3A16IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Model%20comparison%20in%20ANOVA&rft.jtitle=Psychonomic%20bulletin%20&%20review&rft.au=Rouder,%20Jeffrey%20N.&rft.date=2016-12-01&rft.volume=23&rft.issue=6&rft.spage=1779&rft.epage=1786&rft.pages=1779-1786&rft.issn=1069-9384&rft.eissn=1531-5320&rft_id=info:doi/10.3758/s13423-016-1026-5&rft_dat=%3Cproquest_cross%3E1826667695%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1848093748&rft_id=info:pmid/27068543&rfr_iscdi=true |