Statistical analysis of latency outcomes in behavioral experiments
► Methods for analyzing latency outcomes are investigated. ► ANOVA methods may cause biased and misleading results if applied to latency data. ► A survival analysis is proposed to analyze such data. In experimental designs of animal models, memory is often assessed by the time for a performance meas...
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| Veröffentlicht in: | Behavioural brain research 2011-08, Vol.221 (1), p.271-275 |
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| creator | Jahn-Eimermacher, Antje Lasarzik, Irina Raber, Jacob |
| description | ► Methods for analyzing latency outcomes are investigated. ► ANOVA methods may cause biased and misleading results if applied to latency data. ► A survival analysis is proposed to analyze such data.
In experimental designs of animal models, memory is often assessed by the time for a performance measure to occur (latency). Depending on the cognitive test, this may be the time it takes an animal to escape to a hidden platform (water maze), an escape tunnel (Barnes maze) or to enter a dark component (passive avoidance test). Latency outcomes are usually statistically analyzed using ANOVAs. Besides strong distributional assumptions, ANOVA cannot properly deal with animals not showing the performance measure within the trial time, potentially causing biased and misleading results. We propose an alternative approach for statistical analyses of latency outcomes. These analyses have less distributional assumptions and adequately handle results of trials in which the performance measure did not occur within the trial time. The proposed method is well known from survival analyses, provides comprehensible statistical results and allows the generation of meaningful graphs. Experiments of behavioral neuroscience and anesthesiology are used to illustrate this method. |
| doi_str_mv | 10.1016/j.bbr.2011.03.007 |
| format | Article |
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In experimental designs of animal models, memory is often assessed by the time for a performance measure to occur (latency). Depending on the cognitive test, this may be the time it takes an animal to escape to a hidden platform (water maze), an escape tunnel (Barnes maze) or to enter a dark component (passive avoidance test). Latency outcomes are usually statistically analyzed using ANOVAs. Besides strong distributional assumptions, ANOVA cannot properly deal with animals not showing the performance measure within the trial time, potentially causing biased and misleading results. We propose an alternative approach for statistical analyses of latency outcomes. These analyses have less distributional assumptions and adequately handle results of trials in which the performance measure did not occur within the trial time. The proposed method is well known from survival analyses, provides comprehensible statistical results and allows the generation of meaningful graphs. Experiments of behavioral neuroscience and anesthesiology are used to illustrate this method.</description><identifier>ISSN: 0166-4328</identifier><identifier>EISSN: 1872-7549</identifier><identifier>DOI: 10.1016/j.bbr.2011.03.007</identifier><identifier>PMID: 21397635</identifier><identifier>CODEN: BBREDI</identifier><language>eng</language><publisher>Shannon: Elsevier B.V</publisher><subject>Animals ; Avoidance Learning ; Barnes maze ; Behavioral psychophysiology ; Biological and medical sciences ; Data Display - statistics & numerical data ; Data Interpretation, Statistical ; Fundamental and applied biological sciences. Psychology ; Latency ; Maze Learning ; Models, Animal ; Morris water maze ; Passive avoidance ; Psychology. Psychoanalysis. Psychiatry ; Psychology. Psychophysiology ; Reaction Time ; Retention (Psychology) ; Sample Size ; Spatial Behavior ; Statistical analysis</subject><ispartof>Behavioural brain research, 2011-08, Vol.221 (1), p.271-275</ispartof><rights>2011 Elsevier B.V.</rights><rights>2015 INIST-CNRS</rights><rights>Copyright © 2011 Elsevier B.V. All rights reserved.</rights><rights>2011 Elsevier B.V. All rights reserved. 2011</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c578t-e3d17dc9ca0fab23cb952b10a31ba2416993abfc7c619b1254c5e539b40ff00f3</citedby><cites>FETCH-LOGICAL-c578t-e3d17dc9ca0fab23cb952b10a31ba2416993abfc7c619b1254c5e539b40ff00f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.bbr.2011.03.007$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,780,784,885,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=24137838$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21397635$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Jahn-Eimermacher, Antje</creatorcontrib><creatorcontrib>Lasarzik, Irina</creatorcontrib><creatorcontrib>Raber, Jacob</creatorcontrib><title>Statistical analysis of latency outcomes in behavioral experiments</title><title>Behavioural brain research</title><addtitle>Behav Brain Res</addtitle><description>► Methods for analyzing latency outcomes are investigated. ► ANOVA methods may cause biased and misleading results if applied to latency data. ► A survival analysis is proposed to analyze such data.
In experimental designs of animal models, memory is often assessed by the time for a performance measure to occur (latency). Depending on the cognitive test, this may be the time it takes an animal to escape to a hidden platform (water maze), an escape tunnel (Barnes maze) or to enter a dark component (passive avoidance test). Latency outcomes are usually statistically analyzed using ANOVAs. Besides strong distributional assumptions, ANOVA cannot properly deal with animals not showing the performance measure within the trial time, potentially causing biased and misleading results. We propose an alternative approach for statistical analyses of latency outcomes. These analyses have less distributional assumptions and adequately handle results of trials in which the performance measure did not occur within the trial time. The proposed method is well known from survival analyses, provides comprehensible statistical results and allows the generation of meaningful graphs. Experiments of behavioral neuroscience and anesthesiology are used to illustrate this method.</description><subject>Animals</subject><subject>Avoidance Learning</subject><subject>Barnes maze</subject><subject>Behavioral psychophysiology</subject><subject>Biological and medical sciences</subject><subject>Data Display - statistics & numerical data</subject><subject>Data Interpretation, Statistical</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Latency</subject><subject>Maze Learning</subject><subject>Models, Animal</subject><subject>Morris water maze</subject><subject>Passive avoidance</subject><subject>Psychology. Psychoanalysis. Psychiatry</subject><subject>Psychology. Psychophysiology</subject><subject>Reaction Time</subject><subject>Retention (Psychology)</subject><subject>Sample Size</subject><subject>Spatial Behavior</subject><subject>Statistical analysis</subject><issn>0166-4328</issn><issn>1872-7549</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkc2O0zAUhS0EYsrAA7BB2SBWCdc_iWMhIQ0j_qSRWABry3auGVdpXGy3om-Pq5YBNrDywt89PtcfIU8pdBTo8HLdWZs6BpR2wDsAeY-s6ChZK3uh7pNVZYZWcDZekEc5rwFAQE8fkgtGuZID71fkzediSsglODM3ZjHzIYfcRN_MpuDiDk3cFRc3mJuwNBZvzT7EVFH8scUUNriU_Jg88GbO-OR8XpKv795-uf7Q3nx6__H66qZ1vRxLi3yicnLKGfDGMu6s6pmlYDi1hgk6KMWN9U66gSpLWS9cjz1XVoD3AJ5fkten3O3ObnBy9e3aRG9rDZMOOpqg_75Zwq3-FveaU-AjG2vAi3NAit93mIvehOxwns2CcZf1KAfGhGDi_-TApGJCyUrSE-lSzDmhv-tDQR8l6bWukvRRkgauq6Q68-zPRe4mflmpwPMzYHL14pNZXMi_OUG5HPlxoVcnDuu37wMmnV2o1nAKCV3RUwz_qPETlYSwvA</recordid><startdate>20110801</startdate><enddate>20110801</enddate><creator>Jahn-Eimermacher, Antje</creator><creator>Lasarzik, Irina</creator><creator>Raber, Jacob</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>IQODW</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>7X8</scope><scope>7QG</scope><scope>7TK</scope><scope>5PM</scope></search><sort><creationdate>20110801</creationdate><title>Statistical analysis of latency outcomes in behavioral experiments</title><author>Jahn-Eimermacher, Antje ; Lasarzik, Irina ; Raber, Jacob</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c578t-e3d17dc9ca0fab23cb952b10a31ba2416993abfc7c619b1254c5e539b40ff00f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Animals</topic><topic>Avoidance Learning</topic><topic>Barnes maze</topic><topic>Behavioral psychophysiology</topic><topic>Biological and medical sciences</topic><topic>Data Display - statistics & numerical data</topic><topic>Data Interpretation, Statistical</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Latency</topic><topic>Maze Learning</topic><topic>Models, Animal</topic><topic>Morris water maze</topic><topic>Passive avoidance</topic><topic>Psychology. Psychoanalysis. Psychiatry</topic><topic>Psychology. Psychophysiology</topic><topic>Reaction Time</topic><topic>Retention (Psychology)</topic><topic>Sample Size</topic><topic>Spatial Behavior</topic><topic>Statistical analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jahn-Eimermacher, Antje</creatorcontrib><creatorcontrib>Lasarzik, Irina</creatorcontrib><creatorcontrib>Raber, Jacob</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Animal Behavior Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Behavioural brain research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jahn-Eimermacher, Antje</au><au>Lasarzik, Irina</au><au>Raber, Jacob</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Statistical analysis of latency outcomes in behavioral experiments</atitle><jtitle>Behavioural brain research</jtitle><addtitle>Behav Brain Res</addtitle><date>2011-08-01</date><risdate>2011</risdate><volume>221</volume><issue>1</issue><spage>271</spage><epage>275</epage><pages>271-275</pages><issn>0166-4328</issn><eissn>1872-7549</eissn><coden>BBREDI</coden><abstract>► Methods for analyzing latency outcomes are investigated. ► ANOVA methods may cause biased and misleading results if applied to latency data. ► A survival analysis is proposed to analyze such data.
In experimental designs of animal models, memory is often assessed by the time for a performance measure to occur (latency). Depending on the cognitive test, this may be the time it takes an animal to escape to a hidden platform (water maze), an escape tunnel (Barnes maze) or to enter a dark component (passive avoidance test). Latency outcomes are usually statistically analyzed using ANOVAs. Besides strong distributional assumptions, ANOVA cannot properly deal with animals not showing the performance measure within the trial time, potentially causing biased and misleading results. We propose an alternative approach for statistical analyses of latency outcomes. These analyses have less distributional assumptions and adequately handle results of trials in which the performance measure did not occur within the trial time. The proposed method is well known from survival analyses, provides comprehensible statistical results and allows the generation of meaningful graphs. Experiments of behavioral neuroscience and anesthesiology are used to illustrate this method.</abstract><cop>Shannon</cop><pub>Elsevier B.V</pub><pmid>21397635</pmid><doi>10.1016/j.bbr.2011.03.007</doi><tpages>5</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Behavioural brain research, 2011-08, Vol.221 (1), p.271-275 |
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| source | MEDLINE; Access via ScienceDirect (Elsevier) |
| subjects | Animals Avoidance Learning Barnes maze Behavioral psychophysiology Biological and medical sciences Data Display - statistics & numerical data Data Interpretation, Statistical Fundamental and applied biological sciences. Psychology Latency Maze Learning Models, Animal Morris water maze Passive avoidance Psychology. Psychoanalysis. Psychiatry Psychology. Psychophysiology Reaction Time Retention (Psychology) Sample Size Spatial Behavior Statistical analysis |
| title | Statistical analysis of latency outcomes in behavioral experiments |
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