Bayesian inference for psychology. Part II: Example applications with JASP
Bayesian hypothesis testing presents an attractive alternative to p value hypothesis testing. Part I of this series outlined several advantages of Bayesian hypothesis testing, including the ability to quantify evidence and the ability to monitor and update this evidence as data come in, without the...
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Veröffentlicht in: | Psychonomic bulletin & review 2018-02, Vol.25 (1), p.58-76 |
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creator | Wagenmakers, Eric-Jan Love, Jonathon Marsman, Maarten Jamil, Tahira Ly, Alexander Verhagen, Josine Selker, Ravi Gronau, Quentin F. Dropmann, Damian Boutin, Bruno Meerhoff, Frans Knight, Patrick Raj, Akash van Kesteren, Erik-Jan van Doorn, Johnny Šmíra, Martin Epskamp, Sacha Etz, Alexander Matzke, Dora de Jong, Tim van den Bergh, Don Sarafoglou, Alexandra Steingroever, Helen Derks, Koen Rouder, Jeffrey N. Morey, Richard D. |
description | Bayesian hypothesis testing presents an attractive alternative to
p
value hypothesis testing. Part I of this series outlined several advantages of Bayesian hypothesis testing, including the ability to quantify evidence and the ability to monitor and update this evidence as data come in, without the need to know the intention with which the data were collected. Despite these and other practical advantages, Bayesian hypothesis tests are still reported relatively rarely. An important impediment to the widespread adoption of Bayesian tests is arguably the lack of user-friendly software for the run-of-the-mill statistical problems that confront psychologists for the analysis of almost every experiment: the
t
-test, ANOVA, correlation, regression, and contingency tables. In Part II of this series we introduce JASP (
http://www.jasp-stats.org
), an open-source, cross-platform, user-friendly graphical software package that allows users to carry out Bayesian hypothesis tests for standard statistical problems. JASP is based in part on the Bayesian analyses implemented in Morey and Rouder’s BayesFactor package for R. Armed with JASP, the practical advantages of Bayesian hypothesis testing are only a mouse click away. |
doi_str_mv | 10.3758/s13423-017-1323-7 |
format | Article |
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p
value hypothesis testing. Part I of this series outlined several advantages of Bayesian hypothesis testing, including the ability to quantify evidence and the ability to monitor and update this evidence as data come in, without the need to know the intention with which the data were collected. Despite these and other practical advantages, Bayesian hypothesis tests are still reported relatively rarely. An important impediment to the widespread adoption of Bayesian tests is arguably the lack of user-friendly software for the run-of-the-mill statistical problems that confront psychologists for the analysis of almost every experiment: the
t
-test, ANOVA, correlation, regression, and contingency tables. In Part II of this series we introduce JASP (
http://www.jasp-stats.org
), an open-source, cross-platform, user-friendly graphical software package that allows users to carry out Bayesian hypothesis tests for standard statistical problems. JASP is based in part on the Bayesian analyses implemented in Morey and Rouder’s BayesFactor package for R. Armed with JASP, the practical advantages of Bayesian hypothesis testing are only a mouse click away.</description><identifier>ISSN: 1069-9384</identifier><identifier>EISSN: 1531-5320</identifier><identifier>DOI: 10.3758/s13423-017-1323-7</identifier><identifier>PMID: 28685272</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Bayes Theorem ; Bayesian analysis ; Behavioral Science and Psychology ; Brief Report ; Cognitive Psychology ; Experiments ; Humans ; Open access ; Parameter estimation ; Philosophy ; Preferences ; Psychologists ; Psychology ; Research Design ; Researchers ; Science ; Software ; Software packages ; Software upgrading ; Statistical methods ; Theory ; User interface ; Variance analysis</subject><ispartof>Psychonomic bulletin & review, 2018-02, Vol.25 (1), p.58-76</ispartof><rights>The Author(s) 2017</rights><rights>Copyright Springer Nature B.V. Feb 2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3857-23e43a11dad348f2cecfc5252d04009cfd3e9c38111d361cacb34aee420cd5c93</citedby><cites>FETCH-LOGICAL-c3857-23e43a11dad348f2cecfc5252d04009cfd3e9c38111d361cacb34aee420cd5c93</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/s13423-017-1323-7$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.3758/s13423-017-1323-7$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28685272$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wagenmakers, Eric-Jan</creatorcontrib><creatorcontrib>Love, Jonathon</creatorcontrib><creatorcontrib>Marsman, Maarten</creatorcontrib><creatorcontrib>Jamil, Tahira</creatorcontrib><creatorcontrib>Ly, Alexander</creatorcontrib><creatorcontrib>Verhagen, Josine</creatorcontrib><creatorcontrib>Selker, Ravi</creatorcontrib><creatorcontrib>Gronau, Quentin F.</creatorcontrib><creatorcontrib>Dropmann, Damian</creatorcontrib><creatorcontrib>Boutin, Bruno</creatorcontrib><creatorcontrib>Meerhoff, Frans</creatorcontrib><creatorcontrib>Knight, Patrick</creatorcontrib><creatorcontrib>Raj, Akash</creatorcontrib><creatorcontrib>van Kesteren, Erik-Jan</creatorcontrib><creatorcontrib>van Doorn, Johnny</creatorcontrib><creatorcontrib>Šmíra, Martin</creatorcontrib><creatorcontrib>Epskamp, Sacha</creatorcontrib><creatorcontrib>Etz, Alexander</creatorcontrib><creatorcontrib>Matzke, Dora</creatorcontrib><creatorcontrib>de Jong, Tim</creatorcontrib><creatorcontrib>van den Bergh, Don</creatorcontrib><creatorcontrib>Sarafoglou, Alexandra</creatorcontrib><creatorcontrib>Steingroever, Helen</creatorcontrib><creatorcontrib>Derks, Koen</creatorcontrib><creatorcontrib>Rouder, Jeffrey N.</creatorcontrib><creatorcontrib>Morey, Richard D.</creatorcontrib><title>Bayesian inference for psychology. Part II: Example applications with JASP</title><title>Psychonomic bulletin & review</title><addtitle>Psychon Bull Rev</addtitle><addtitle>Psychon Bull Rev</addtitle><description>Bayesian hypothesis testing presents an attractive alternative to
p
value hypothesis testing. Part I of this series outlined several advantages of Bayesian hypothesis testing, including the ability to quantify evidence and the ability to monitor and update this evidence as data come in, without the need to know the intention with which the data were collected. Despite these and other practical advantages, Bayesian hypothesis tests are still reported relatively rarely. An important impediment to the widespread adoption of Bayesian tests is arguably the lack of user-friendly software for the run-of-the-mill statistical problems that confront psychologists for the analysis of almost every experiment: the
t
-test, ANOVA, correlation, regression, and contingency tables. In Part II of this series we introduce JASP (
http://www.jasp-stats.org
), an open-source, cross-platform, user-friendly graphical software package that allows users to carry out Bayesian hypothesis tests for standard statistical problems. JASP is based in part on the Bayesian analyses implemented in Morey and Rouder’s BayesFactor package for R. Armed with JASP, the practical advantages of Bayesian hypothesis testing are only a mouse click away.</description><subject>Bayes Theorem</subject><subject>Bayesian analysis</subject><subject>Behavioral Science and Psychology</subject><subject>Brief Report</subject><subject>Cognitive Psychology</subject><subject>Experiments</subject><subject>Humans</subject><subject>Open access</subject><subject>Parameter estimation</subject><subject>Philosophy</subject><subject>Preferences</subject><subject>Psychologists</subject><subject>Psychology</subject><subject>Research Design</subject><subject>Researchers</subject><subject>Science</subject><subject>Software</subject><subject>Software packages</subject><subject>Software upgrading</subject><subject>Statistical methods</subject><subject>Theory</subject><subject>User interface</subject><subject>Variance analysis</subject><issn>1069-9384</issn><issn>1531-5320</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp1kd9LHDEQx4O0qLX9A3wpgb70ZW2SSXY3fRBUbD0RFNo-h5idvYvsJWuy1_b--0bO-gt8ysB85psZPoTsc3YAjWq_ZA5SQMV4U3EoRbNFdrkCXikQ7E2pWa0rDa3cIe9yvmGMqVrX22RHtHWrRCN2yfmxXWP2NlAfekwYHNI-JjrmtVvEIc7XB_TKponOZl_p6V-7HAekdhwH7-zkY8j0j58W9Pzox9V78ra3Q8YP9-8e-fXt9OfJWXVx-X12cnRROWhVUwlACZbzznYg2144dL1TQomOSca06ztAXVBeEKi5s-4apEWUgrlOOQ175HCTO66ul9g5DFOygxmTX9q0NtF687wT_MLM42-j2lpoUZeAz_cBKd6uME9m6bPDYbAB4yobrnkDtZISCvrpBXoTVymU84woGAjFdVsovqFcijkn7B-W4czcmTIbU6aYMnemTFNmPj694mHiv5oCiA2QSyvMMT1-_XrqP3K8nlI</recordid><startdate>20180201</startdate><enddate>20180201</enddate><creator>Wagenmakers, Eric-Jan</creator><creator>Love, Jonathon</creator><creator>Marsman, Maarten</creator><creator>Jamil, Tahira</creator><creator>Ly, Alexander</creator><creator>Verhagen, Josine</creator><creator>Selker, Ravi</creator><creator>Gronau, Quentin F.</creator><creator>Dropmann, Damian</creator><creator>Boutin, Bruno</creator><creator>Meerhoff, Frans</creator><creator>Knight, Patrick</creator><creator>Raj, Akash</creator><creator>van Kesteren, Erik-Jan</creator><creator>van Doorn, Johnny</creator><creator>Šmíra, Martin</creator><creator>Epskamp, Sacha</creator><creator>Etz, Alexander</creator><creator>Matzke, Dora</creator><creator>de Jong, Tim</creator><creator>van den Bergh, Don</creator><creator>Sarafoglou, Alexandra</creator><creator>Steingroever, Helen</creator><creator>Derks, Koen</creator><creator>Rouder, Jeffrey N.</creator><creator>Morey, Richard D.</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>C6C</scope><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><scope>5PM</scope></search><sort><creationdate>20180201</creationdate><title>Bayesian inference for psychology. Part II: Example applications with JASP</title><author>Wagenmakers, Eric-Jan ; Love, Jonathon ; Marsman, Maarten ; Jamil, Tahira ; Ly, Alexander ; Verhagen, Josine ; Selker, Ravi ; Gronau, Quentin F. ; Dropmann, Damian ; Boutin, Bruno ; Meerhoff, Frans ; Knight, Patrick ; Raj, Akash ; van Kesteren, Erik-Jan ; van Doorn, Johnny ; Šmíra, Martin ; Epskamp, Sacha ; Etz, Alexander ; Matzke, Dora ; de Jong, Tim ; van den Bergh, Don ; Sarafoglou, Alexandra ; Steingroever, Helen ; Derks, Koen ; Rouder, Jeffrey N. ; Morey, Richard D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3857-23e43a11dad348f2cecfc5252d04009cfd3e9c38111d361cacb34aee420cd5c93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Bayes Theorem</topic><topic>Bayesian analysis</topic><topic>Behavioral Science and Psychology</topic><topic>Brief Report</topic><topic>Cognitive Psychology</topic><topic>Experiments</topic><topic>Humans</topic><topic>Open access</topic><topic>Parameter estimation</topic><topic>Philosophy</topic><topic>Preferences</topic><topic>Psychologists</topic><topic>Psychology</topic><topic>Research Design</topic><topic>Researchers</topic><topic>Science</topic><topic>Software</topic><topic>Software packages</topic><topic>Software upgrading</topic><topic>Statistical methods</topic><topic>Theory</topic><topic>User interface</topic><topic>Variance analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wagenmakers, Eric-Jan</creatorcontrib><creatorcontrib>Love, Jonathon</creatorcontrib><creatorcontrib>Marsman, Maarten</creatorcontrib><creatorcontrib>Jamil, Tahira</creatorcontrib><creatorcontrib>Ly, Alexander</creatorcontrib><creatorcontrib>Verhagen, Josine</creatorcontrib><creatorcontrib>Selker, Ravi</creatorcontrib><creatorcontrib>Gronau, Quentin F.</creatorcontrib><creatorcontrib>Dropmann, Damian</creatorcontrib><creatorcontrib>Boutin, Bruno</creatorcontrib><creatorcontrib>Meerhoff, Frans</creatorcontrib><creatorcontrib>Knight, Patrick</creatorcontrib><creatorcontrib>Raj, Akash</creatorcontrib><creatorcontrib>van Kesteren, Erik-Jan</creatorcontrib><creatorcontrib>van Doorn, Johnny</creatorcontrib><creatorcontrib>Šmíra, Martin</creatorcontrib><creatorcontrib>Epskamp, Sacha</creatorcontrib><creatorcontrib>Etz, Alexander</creatorcontrib><creatorcontrib>Matzke, Dora</creatorcontrib><creatorcontrib>de Jong, Tim</creatorcontrib><creatorcontrib>van den Bergh, Don</creatorcontrib><creatorcontrib>Sarafoglou, Alexandra</creatorcontrib><creatorcontrib>Steingroever, Helen</creatorcontrib><creatorcontrib>Derks, Koen</creatorcontrib><creatorcontrib>Rouder, Jeffrey N.</creatorcontrib><creatorcontrib>Morey, Richard D.</creatorcontrib><collection>Springer Nature OA Free Journals</collection><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 - 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Part II: Example applications with JASP</atitle><jtitle>Psychonomic bulletin & review</jtitle><stitle>Psychon Bull Rev</stitle><addtitle>Psychon Bull Rev</addtitle><date>2018-02-01</date><risdate>2018</risdate><volume>25</volume><issue>1</issue><spage>58</spage><epage>76</epage><pages>58-76</pages><issn>1069-9384</issn><eissn>1531-5320</eissn><abstract>Bayesian hypothesis testing presents an attractive alternative to
p
value hypothesis testing. Part I of this series outlined several advantages of Bayesian hypothesis testing, including the ability to quantify evidence and the ability to monitor and update this evidence as data come in, without the need to know the intention with which the data were collected. Despite these and other practical advantages, Bayesian hypothesis tests are still reported relatively rarely. An important impediment to the widespread adoption of Bayesian tests is arguably the lack of user-friendly software for the run-of-the-mill statistical problems that confront psychologists for the analysis of almost every experiment: the
t
-test, ANOVA, correlation, regression, and contingency tables. In Part II of this series we introduce JASP (
http://www.jasp-stats.org
), an open-source, cross-platform, user-friendly graphical software package that allows users to carry out Bayesian hypothesis tests for standard statistical problems. JASP is based in part on the Bayesian analyses implemented in Morey and Rouder’s BayesFactor package for R. Armed with JASP, the practical advantages of Bayesian hypothesis testing are only a mouse click away.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>28685272</pmid><doi>10.3758/s13423-017-1323-7</doi><tpages>19</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Bayes Theorem Bayesian analysis Behavioral Science and Psychology Brief Report Cognitive Psychology Experiments Humans Open access Parameter estimation Philosophy Preferences Psychologists Psychology Research Design Researchers Science Software Software packages Software upgrading Statistical methods Theory User interface Variance analysis |
title | Bayesian inference for psychology. Part II: Example applications with JASP |
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