Relative risk estimated from the ratio of two median unbiased estimates
Clinical trials often include binary end points. In some cases, no successes are observed and the usual large sample estimates of relative risk are undefined. The paper proposes an estimator for relative risk based on the median unbiased estimator. The relative risk estimator proposed is well define...
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| Veröffentlicht in: | Applied statistics 2010-08, Vol.59 (4), p.657-671 |
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| creator | Carter, Rickey E. Lin, Yan Lipsitz, Stuart R. Newcombe, Robert G. Hermayer, Kathie L. |
| description | Clinical trials often include binary end points. In some cases, no successes are observed and the usual large sample estimates of relative risk are undefined. The paper proposes an estimator for relative risk based on the median unbiased estimator. The relative risk estimator proposed is well defined and performs satisfactorily for a wide range of data configurations. To facilitate the use of the estimator, a deterministic bootstrap confidence interval is also proposed, and an SAS macro is available to perform the necessary calculations. An on-going randomized clinical trial motivated the development of the estimator and is used to illustrate the approach. |
| doi_str_mv | 10.1111/j.1467-9876.2010.00711.x |
| format | Article |
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In some cases, no successes are observed and the usual large sample estimates of relative risk are undefined. The paper proposes an estimator for relative risk based on the median unbiased estimator. The relative risk estimator proposed is well defined and performs satisfactorily for a wide range of data configurations. To facilitate the use of the estimator, a deterministic bootstrap confidence interval is also proposed, and an SAS macro is available to perform the necessary calculations. 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Ordered structures ; Confidence interval ; Confidence intervals ; Coverage probability ; Designs and configurations ; Estimates ; Estimating techniques ; Estimation ; Estimators ; Exact sciences and technology ; Interval estimators ; Mathematical analysis ; Mathematics ; Median unbiased estimator ; Medical sciences ; Null hypothesis ; Parametric inference ; Point estimators ; Probability ; Probability and statistics ; Ratio scales ; Relative risk ; Risk ; Risk management ; Sample size ; Samples ; Sciences and techniques of general use ; Shrinkage ; Shrinkage estimator ; Statistical analysis ; Statistics ; Studies ; Unbiased estimators</subject><ispartof>Applied statistics, 2010-08, Vol.59 (4), p.657-671</ispartof><rights>2010 The Royal Statistical Society and Blackwell Publishing Ltd.</rights><rights>2010 Royal Statistical Society</rights><rights>2015 INIST-CNRS</rights><rights>2010 The Royal Statistical Society and Blackwell Publishing Ltd</rights><rights>Copyright 2009, Mayo Foundation for Medical Education and Research 2009</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c7551-af8f45fc2c06895e6ebd46b677ba1ccec8299d8aff14ba0601adb0bdfc893cb23</citedby><cites>FETCH-LOGICAL-c7551-af8f45fc2c06895e6ebd46b677ba1ccec8299d8aff14ba0601adb0bdfc893cb23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/40783096$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/40783096$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,315,781,785,804,833,886,1418,4009,27929,27930,45579,45580,58022,58026,58255,58259</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=23047049$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/20711511$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttp://econpapers.repec.org/article/blajorssc/v_3a59_3ay_3a2010_3ai_3a4_3ap_3a657-671.htm$$DView record in RePEc$$Hfree_for_read</backlink></links><search><creatorcontrib>Carter, Rickey E.</creatorcontrib><creatorcontrib>Lin, Yan</creatorcontrib><creatorcontrib>Lipsitz, Stuart R.</creatorcontrib><creatorcontrib>Newcombe, Robert G.</creatorcontrib><creatorcontrib>Hermayer, Kathie L.</creatorcontrib><title>Relative risk estimated from the ratio of two median unbiased estimates</title><title>Applied statistics</title><addtitle>J R Stat Soc Ser C Appl Stat</addtitle><description>Clinical trials often include binary end points. In some cases, no successes are observed and the usual large sample estimates of relative risk are undefined. The paper proposes an estimator for relative risk based on the median unbiased estimator. The relative risk estimator proposed is well defined and performs satisfactorily for a wide range of data configurations. To facilitate the use of the estimator, a deterministic bootstrap confidence interval is also proposed, and an SAS macro is available to perform the necessary calculations. An on-going randomized clinical trial motivated the development of the estimator and is used to illustrate the approach.</description><subject>Analytical estimating</subject><subject>Applications</subject><subject>Applied statistics</subject><subject>Binomial distribution</subject><subject>Binomials</subject><subject>Biology, psychology, social sciences</subject><subject>Bootstrap method</subject><subject>Clinical interviews</subject><subject>Clinical trials</subject><subject>Combinatorics</subject><subject>Combinatorics. Ordered structures</subject><subject>Confidence interval</subject><subject>Confidence intervals</subject><subject>Coverage probability</subject><subject>Designs and configurations</subject><subject>Estimates</subject><subject>Estimating techniques</subject><subject>Estimation</subject><subject>Estimators</subject><subject>Exact sciences and technology</subject><subject>Interval estimators</subject><subject>Mathematical analysis</subject><subject>Mathematics</subject><subject>Median unbiased estimator</subject><subject>Medical sciences</subject><subject>Null hypothesis</subject><subject>Parametric inference</subject><subject>Point estimators</subject><subject>Probability</subject><subject>Probability and statistics</subject><subject>Ratio scales</subject><subject>Relative risk</subject><subject>Risk</subject><subject>Risk management</subject><subject>Sample size</subject><subject>Samples</subject><subject>Sciences and techniques of general use</subject><subject>Shrinkage</subject><subject>Shrinkage estimator</subject><subject>Statistical analysis</subject><subject>Statistics</subject><subject>Studies</subject><subject>Unbiased estimators</subject><issn>0035-9254</issn><issn>1467-9876</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>X2L</sourceid><recordid>eNqNktuO0zAQhiMEYsvCI4AiJAQ3KXbi48UioQpa2NUidTlcWo7j0HTTuNhpt317Jk03HC5YLE0i-f_-ycxkoijGaIzhvF6OMWE8kYKzcYrgFiGO8Xh3LxoNwv1ohFBGE5lSchI9CmGJ4GBEHkYnaYdTjEfRdG5r3VZbG_sqXMc2tNVKt7aIS-9WcbuAe5Bd7Mq4vXHxyhaVbuJNk1c6AHXLh8fRg1LXwT45vk-jL-_ffZ7MkotP0w-TtxeJ4ZTiRJeiJLQ0qUFMSGqZzQvCcsZ5rrEx1ohUykLossQk14ghrIsc5UVphMxMnman0Zs-73qTQzHGNq3XtVp7KMPvldOV-lNpqoX67rYqlVhI1CV4eUzg3Y8N1K9WVTC2rnVj3SYoiRnFhDB0J8kpEZxLKYB89U8Si5RhyhiTd6OM44xkMiWAPv8LXbqNb2C6iqdAcIm7dkQPGe9C8LYcRoGR6nZFLVW3EqpbCdXtijrsitqB9WNv9XZtzeDLa710PgSjtirTVMJjD3GwZjDeTBOINQSjXEG5atGuINmz3__LkO120wB4cQR0MLouvW5MFX5xGSIckW5AZz13U9V2_9_dqPnV1YQfvvO09y9D6_zgJ4iLDEkGetLrVWjtbtC1v4ZeMk7Vt8upmsnzr2g-u1Tn2U_QHwxF</recordid><startdate>201008</startdate><enddate>201008</enddate><creator>Carter, Rickey E.</creator><creator>Lin, Yan</creator><creator>Lipsitz, Stuart R.</creator><creator>Newcombe, Robert G.</creator><creator>Hermayer, Kathie L.</creator><general>Blackwell Publishing Ltd</general><general>Wiley-Blackwell</general><general>Royal Statistical Society</general><general>Oxford University Press</general><scope>BSCLL</scope><scope>IQODW</scope><scope>NPM</scope><scope>DKI</scope><scope>X2L</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8BJ</scope><scope>8FD</scope><scope>FQK</scope><scope>JBE</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7X8</scope><scope>7U1</scope><scope>7U2</scope><scope>C1K</scope><scope>5PM</scope></search><sort><creationdate>201008</creationdate><title>Relative risk estimated from the ratio of two median unbiased estimates</title><author>Carter, Rickey E. ; Lin, Yan ; Lipsitz, Stuart R. ; Newcombe, Robert G. ; Hermayer, Kathie L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c7551-af8f45fc2c06895e6ebd46b677ba1ccec8299d8aff14ba0601adb0bdfc893cb23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Analytical estimating</topic><topic>Applications</topic><topic>Applied statistics</topic><topic>Binomial distribution</topic><topic>Binomials</topic><topic>Biology, psychology, social sciences</topic><topic>Bootstrap method</topic><topic>Clinical interviews</topic><topic>Clinical trials</topic><topic>Combinatorics</topic><topic>Combinatorics. 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| source | Wiley-Blackwell Journals; RePEc; Business Source Complete; JSTOR Mathematics & Statistics; JSTOR; Oxford Journals |
| subjects | Analytical estimating Applications Applied statistics Binomial distribution Binomials Biology, psychology, social sciences Bootstrap method Clinical interviews Clinical trials Combinatorics Combinatorics. Ordered structures Confidence interval Confidence intervals Coverage probability Designs and configurations Estimates Estimating techniques Estimation Estimators Exact sciences and technology Interval estimators Mathematical analysis Mathematics Median unbiased estimator Medical sciences Null hypothesis Parametric inference Point estimators Probability Probability and statistics Ratio scales Relative risk Risk Risk management Sample size Samples Sciences and techniques of general use Shrinkage Shrinkage estimator Statistical analysis Statistics Studies Unbiased estimators |
| title | Relative risk estimated from the ratio of two median unbiased estimates |
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