A confidence interval approach to sample size estimation for interobserver agreement studies with multiple raters and outcomes
Abstract Objective Studies measuring interobserver agreement (reliability) are common in clinical practice, yet discussion of appropriate sample size estimation techniques is minimal as compared with clinical trials. The authors propose a sample size estimation technique to achieve a prespecified lo...
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description | Abstract Objective Studies measuring interobserver agreement (reliability) are common in clinical practice, yet discussion of appropriate sample size estimation techniques is minimal as compared with clinical trials. The authors propose a sample size estimation technique to achieve a prespecified lower and upper limit for a confidence interval for the κ coefficient in studies of interobserver agreement. Study Design and Setting The proposed technique can be used to design a study measuring interobserver agreement with any number of outcomes and any number of raters. Potential application areas include: pathology, psychiatry, dentistry, and physical therapy. Results This technique is illustrated using two examples. The first considers a pilot study in oral radiology, whose authors studied the reliability of the mandibular cortical index as measured by three dental professionals. The second example examines the level of interobserver agreement among four nurses with respect to five triage levels used in the Canadian Triage and Acuity Scale. Conclusion This method should be useful in the planning stages of an interobserver agreement study in which the investigator would like to obtain a prespecified level of precision in the estimation of κ . An R software package (R Foundation for Statistical Computing, Vienna, Austria), kappaSize is also provided that implements this method. |
doi_str_mv | 10.1016/j.jclinepi.2011.10.019 |
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The authors propose a sample size estimation technique to achieve a prespecified lower and upper limit for a confidence interval for the κ coefficient in studies of interobserver agreement. Study Design and Setting The proposed technique can be used to design a study measuring interobserver agreement with any number of outcomes and any number of raters. Potential application areas include: pathology, psychiatry, dentistry, and physical therapy. Results This technique is illustrated using two examples. The first considers a pilot study in oral radiology, whose authors studied the reliability of the mandibular cortical index as measured by three dental professionals. The second example examines the level of interobserver agreement among four nurses with respect to five triage levels used in the Canadian Triage and Acuity Scale. Conclusion This method should be useful in the planning stages of an interobserver agreement study in which the investigator would like to obtain a prespecified level of precision in the estimation of κ . An R software package (R Foundation for Statistical Computing, Vienna, Austria), kappaSize is also provided that implements this method.</description><identifier>ISSN: 0895-4356</identifier><identifier>EISSN: 1878-5921</identifier><identifier>DOI: 10.1016/j.jclinepi.2011.10.019</identifier><identifier>PMID: 22560852</identifier><language>eng</language><publisher>New York, NY: Elsevier Inc</publisher><subject>Acuity ; Agreement ; Agreements ; Biological and medical sciences ; Canada - epidemiology ; Clinical trials ; Confidence Intervals ; Cortex ; Dentistry ; Epidemiology ; Estimates ; Expected values ; Experimental design ; General aspects ; Humans ; Hypotheses ; Hypothesis testing ; Internal Medicine ; Kappa ; Mandible ; Mandible - diagnostic imaging ; Mathematical Computing ; Medical research ; Medical sciences ; Observer Variation ; Physical education ; Pilot Projects ; Planification. Prevention (methods). Intervention. Evaluation ; Psychiatry ; Public health. Hygiene ; Public health. Hygiene-occupational medicine ; Radiography, Dental - statistics & numerical data ; Radiography, Panoramic - statistics & numerical data ; Radiology ; Reliability ; Reproducibility of Results ; Sample Size ; Sample size estimation ; Sensitivity analysis ; Software packages ; Statistical analysis ; Studies</subject><ispartof>Journal of clinical epidemiology, 2012-07, Vol.65 (7), p.778-784</ispartof><rights>Elsevier Inc.</rights><rights>2012 Elsevier Inc.</rights><rights>2015 INIST-CNRS</rights><rights>Copyright © 2012 Elsevier Inc. All rights reserved.</rights><rights>Copyright Elsevier Science Ltd. Jul 2012</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c509t-46b5c0de339c945f3efc63103c9469749c8b842deb0c3f4720912d9e5688ead83</citedby><cites>FETCH-LOGICAL-c509t-46b5c0de339c945f3efc63103c9469749c8b842deb0c3f4720912d9e5688ead83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0895435612000248$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=25968922$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/22560852$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Rotondi, Michael A</creatorcontrib><creatorcontrib>Donner, Allan</creatorcontrib><title>A confidence interval approach to sample size estimation for interobserver agreement studies with multiple raters and outcomes</title><title>Journal of clinical epidemiology</title><addtitle>J Clin Epidemiol</addtitle><description>Abstract Objective Studies measuring interobserver agreement (reliability) are common in clinical practice, yet discussion of appropriate sample size estimation techniques is minimal as compared with clinical trials. The authors propose a sample size estimation technique to achieve a prespecified lower and upper limit for a confidence interval for the κ coefficient in studies of interobserver agreement. Study Design and Setting The proposed technique can be used to design a study measuring interobserver agreement with any number of outcomes and any number of raters. Potential application areas include: pathology, psychiatry, dentistry, and physical therapy. Results This technique is illustrated using two examples. The first considers a pilot study in oral radiology, whose authors studied the reliability of the mandibular cortical index as measured by three dental professionals. The second example examines the level of interobserver agreement among four nurses with respect to five triage levels used in the Canadian Triage and Acuity Scale. Conclusion This method should be useful in the planning stages of an interobserver agreement study in which the investigator would like to obtain a prespecified level of precision in the estimation of κ . An R software package (R Foundation for Statistical Computing, Vienna, Austria), kappaSize is also provided that implements this method.</description><subject>Acuity</subject><subject>Agreement</subject><subject>Agreements</subject><subject>Biological and medical sciences</subject><subject>Canada - epidemiology</subject><subject>Clinical trials</subject><subject>Confidence Intervals</subject><subject>Cortex</subject><subject>Dentistry</subject><subject>Epidemiology</subject><subject>Estimates</subject><subject>Expected values</subject><subject>Experimental design</subject><subject>General aspects</subject><subject>Humans</subject><subject>Hypotheses</subject><subject>Hypothesis testing</subject><subject>Internal Medicine</subject><subject>Kappa</subject><subject>Mandible</subject><subject>Mandible - diagnostic imaging</subject><subject>Mathematical Computing</subject><subject>Medical research</subject><subject>Medical sciences</subject><subject>Observer Variation</subject><subject>Physical education</subject><subject>Pilot Projects</subject><subject>Planification. Prevention (methods). Intervention. Evaluation</subject><subject>Psychiatry</subject><subject>Public health. Hygiene</subject><subject>Public health. Hygiene-occupational medicine</subject><subject>Radiography, Dental - statistics & numerical data</subject><subject>Radiography, Panoramic - statistics & numerical data</subject><subject>Radiology</subject><subject>Reliability</subject><subject>Reproducibility of Results</subject><subject>Sample Size</subject><subject>Sample size estimation</subject><subject>Sensitivity analysis</subject><subject>Software packages</subject><subject>Statistical analysis</subject><subject>Studies</subject><issn>0895-4356</issn><issn>1878-5921</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqFkk2L1TAUhoMoznX0LwwBEdz0mo8mTTbiMPgFAy7UdUjTUye1bWqSjowLf7sp944Ds9BVyOE57_l4D0JnlOwpofLVsB_c6GdY_J4RSktwT6h-gHZUNaoSmtGHaEeUFlXNhTxBT1IaCKENacRjdMKYkEQJtkO_z7ELc-87mB1gP2eI13bEdllisO4K54CTnZYRcPK_AEPKfrLZhxn3IR740KaSBBHbbxFggjnjlNfOQ8I_fb7C0zpmvylEW-iE7dzhsGYXJkhP0aPejgmeHd9T9PXd2y8XH6rLT-8_XpxfVk4QnatatsKRDjjXTtei59A7ySnh5Sd1U2unWlWzDlrieF83jGjKOg1CKgW2U_wUvTzolrF-rGUKM_nkYBztDGFNpuxUcdnUDS_o83voENY4l-4MI4xLroiW_6JKW1JLJvVWVh4oF0NKEXqzxLK_eFOgraY0g7n10Ww-bvHiY0k8O8qv7QTd37Rb4wrw4gjY5OzYRzs7n-44oaXSbOPeHDgo2732EE1yfvO68xFcNl3w_-_l9T2JjfKl6ne4gXQ3t0nMEPN5u7rt6CgjhLBa8T-3y9St</recordid><startdate>20120701</startdate><enddate>20120701</enddate><creator>Rotondi, Michael A</creator><creator>Donner, Allan</creator><general>Elsevier Inc</general><general>Elsevier</general><general>Elsevier Limited</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>3V.</scope><scope>7QL</scope><scope>7QP</scope><scope>7RV</scope><scope>7T2</scope><scope>7T7</scope><scope>7TK</scope><scope>7U7</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88C</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>M2O</scope><scope>M7N</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope></search><sort><creationdate>20120701</creationdate><title>A confidence interval approach to sample size estimation for interobserver agreement studies with multiple raters and outcomes</title><author>Rotondi, Michael A ; Donner, Allan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c509t-46b5c0de339c945f3efc63103c9469749c8b842deb0c3f4720912d9e5688ead83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Acuity</topic><topic>Agreement</topic><topic>Agreements</topic><topic>Biological and medical sciences</topic><topic>Canada - epidemiology</topic><topic>Clinical trials</topic><topic>Confidence Intervals</topic><topic>Cortex</topic><topic>Dentistry</topic><topic>Epidemiology</topic><topic>Estimates</topic><topic>Expected values</topic><topic>Experimental design</topic><topic>General aspects</topic><topic>Humans</topic><topic>Hypotheses</topic><topic>Hypothesis testing</topic><topic>Internal Medicine</topic><topic>Kappa</topic><topic>Mandible</topic><topic>Mandible - diagnostic imaging</topic><topic>Mathematical Computing</topic><topic>Medical research</topic><topic>Medical sciences</topic><topic>Observer Variation</topic><topic>Physical education</topic><topic>Pilot Projects</topic><topic>Planification. Prevention (methods). Intervention. Evaluation</topic><topic>Psychiatry</topic><topic>Public health. Hygiene</topic><topic>Public health. Hygiene-occupational medicine</topic><topic>Radiography, Dental - statistics & numerical data</topic><topic>Radiography, Panoramic - statistics & numerical data</topic><topic>Radiology</topic><topic>Reliability</topic><topic>Reproducibility of Results</topic><topic>Sample Size</topic><topic>Sample size estimation</topic><topic>Sensitivity analysis</topic><topic>Software packages</topic><topic>Statistical analysis</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rotondi, Michael A</creatorcontrib><creatorcontrib>Donner, Allan</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>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Neurosciences Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</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 One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</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>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Healthcare Administration Database</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Research Library (Corporate)</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</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 Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of clinical epidemiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rotondi, Michael A</au><au>Donner, Allan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A confidence interval approach to sample size estimation for interobserver agreement studies with multiple raters and outcomes</atitle><jtitle>Journal of clinical epidemiology</jtitle><addtitle>J Clin Epidemiol</addtitle><date>2012-07-01</date><risdate>2012</risdate><volume>65</volume><issue>7</issue><spage>778</spage><epage>784</epage><pages>778-784</pages><issn>0895-4356</issn><eissn>1878-5921</eissn><abstract>Abstract Objective Studies measuring interobserver agreement (reliability) are common in clinical practice, yet discussion of appropriate sample size estimation techniques is minimal as compared with clinical trials. The authors propose a sample size estimation technique to achieve a prespecified lower and upper limit for a confidence interval for the κ coefficient in studies of interobserver agreement. Study Design and Setting The proposed technique can be used to design a study measuring interobserver agreement with any number of outcomes and any number of raters. Potential application areas include: pathology, psychiatry, dentistry, and physical therapy. Results This technique is illustrated using two examples. The first considers a pilot study in oral radiology, whose authors studied the reliability of the mandibular cortical index as measured by three dental professionals. The second example examines the level of interobserver agreement among four nurses with respect to five triage levels used in the Canadian Triage and Acuity Scale. Conclusion This method should be useful in the planning stages of an interobserver agreement study in which the investigator would like to obtain a prespecified level of precision in the estimation of κ . An R software package (R Foundation for Statistical Computing, Vienna, Austria), kappaSize is also provided that implements this method.</abstract><cop>New York, NY</cop><pub>Elsevier Inc</pub><pmid>22560852</pmid><doi>10.1016/j.jclinepi.2011.10.019</doi><tpages>7</tpages></addata></record> |
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subjects | Acuity Agreement Agreements Biological and medical sciences Canada - epidemiology Clinical trials Confidence Intervals Cortex Dentistry Epidemiology Estimates Expected values Experimental design General aspects Humans Hypotheses Hypothesis testing Internal Medicine Kappa Mandible Mandible - diagnostic imaging Mathematical Computing Medical research Medical sciences Observer Variation Physical education Pilot Projects Planification. Prevention (methods). Intervention. Evaluation Psychiatry Public health. Hygiene Public health. Hygiene-occupational medicine Radiography, Dental - statistics & numerical data Radiography, Panoramic - statistics & numerical data Radiology Reliability Reproducibility of Results Sample Size Sample size estimation Sensitivity analysis Software packages Statistical analysis Studies |
title | A confidence interval approach to sample size estimation for interobserver agreement studies with multiple raters and outcomes |
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