A Nonparametric Test for Independence of Time to Failure and Cause of Failure of Current Status Competing Risks Data
Abtsrcat Competing risks data are common in medical research in which lifetime of individuals can be classied in terms of causes of failure. Current status censoring occurs, if patients (objects) in a study are observed only once at a random monitoring time and only the information whether the event...
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| Veröffentlicht in: | Bulletin - Calcutta Statistical Association 2012-09, Vol.64 (3-4), p.167-180 |
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| container_title | Bulletin - Calcutta Statistical Association |
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| creator | Sreedevi, E.P. Sankaran, P.G. Dhanavanthan, P. |
| description | Abtsrcat
Competing risks data are common in medical research in which lifetime of individuals can be classied in terms of causes of failure. Current status censoring occurs, if patients (objects) in a study are observed only once at a random monitoring time and only the information whether the event of interest has occurred or not prior to the monitoring time is available. Such data arise frequently from cross sectional studies in demography, epidemiology and reliability studies. In the present paper, we study current status data with competing risks. We develop a non parametric test for independence of time to failure and cause of failure of current status competing risks data. The asymptotic property of the test statistic is also discussed. Simulation studies and a real data example illustrate the practical utility of the procedure. |
| doi_str_mv | 10.1177/0008068320120302 |
| format | Article |
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Competing risks data are common in medical research in which lifetime of individuals can be classied in terms of causes of failure. Current status censoring occurs, if patients (objects) in a study are observed only once at a random monitoring time and only the information whether the event of interest has occurred or not prior to the monitoring time is available. Such data arise frequently from cross sectional studies in demography, epidemiology and reliability studies. In the present paper, we study current status data with competing risks. We develop a non parametric test for independence of time to failure and cause of failure of current status competing risks data. The asymptotic property of the test statistic is also discussed. Simulation studies and a real data example illustrate the practical utility of the procedure.</description><identifier>ISSN: 0008-0683</identifier><identifier>EISSN: 2456-6462</identifier><identifier>DOI: 10.1177/0008068320120302</identifier><language>eng</language><publisher>New Delhi, India: SAGE Publications</publisher><ispartof>Bulletin - Calcutta Statistical Association, 2012-09, Vol.64 (3-4), p.167-180</ispartof><rights>2012 SAGE Publications</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2382-fa6803101a0018ea96d9c88d6e1a0ea376202033d48d29d7331b1374a17a1c293</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/0008068320120302$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/0008068320120302$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>314,776,780,21800,27903,27904,43600,43601</link.rule.ids></links><search><creatorcontrib>Sreedevi, E.P.</creatorcontrib><creatorcontrib>Sankaran, P.G.</creatorcontrib><creatorcontrib>Dhanavanthan, P.</creatorcontrib><title>A Nonparametric Test for Independence of Time to Failure and Cause of Failure of Current Status Competing Risks Data</title><title>Bulletin - Calcutta Statistical Association</title><description>Abtsrcat
Competing risks data are common in medical research in which lifetime of individuals can be classied in terms of causes of failure. Current status censoring occurs, if patients (objects) in a study are observed only once at a random monitoring time and only the information whether the event of interest has occurred or not prior to the monitoring time is available. Such data arise frequently from cross sectional studies in demography, epidemiology and reliability studies. In the present paper, we study current status data with competing risks. We develop a non parametric test for independence of time to failure and cause of failure of current status competing risks data. The asymptotic property of the test statistic is also discussed. Simulation studies and a real data example illustrate the practical utility of the procedure.</description><issn>0008-0683</issn><issn>2456-6462</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><recordid>eNp1UE1PwzAMjRBITGN3jvkDBSfp0vQ4FQaTJpCgnCuvcafC2lRJeuDf0zG4IHGxrfdh2Y-xawE3QmTZLQAY0EZJEBIUyDM2k-lSJzrV8pzNjnRy5C_ZIoR2N0lyaYxezlhc8SfXD-ixo-jbmpcUIm-c55ve0kBT6WviruFl2xGPjq-xPYyeOPaWFziGb_IXnMZi9J76yF8jxjHwwnUDxbbf85c2fAR-hxGv2EWDh0CLnz5nb-v7snhMts8Pm2K1TWqpjEwa1AaUAIEAwhDm2ua1MVbThBCqTEuY3lU2NVbmNlNK7ITKUhQZilrmas7gtLf2LgRPTTX4tkP_WQmojsFVf4ObLMnJEnBP1bsbfT9d-L_-Cwsya8g</recordid><startdate>201209</startdate><enddate>201209</enddate><creator>Sreedevi, E.P.</creator><creator>Sankaran, P.G.</creator><creator>Dhanavanthan, P.</creator><general>SAGE Publications</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>201209</creationdate><title>A Nonparametric Test for Independence of Time to Failure and Cause of Failure of Current Status Competing Risks Data</title><author>Sreedevi, E.P. ; Sankaran, P.G. ; Dhanavanthan, P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2382-fa6803101a0018ea96d9c88d6e1a0ea376202033d48d29d7331b1374a17a1c293</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sreedevi, E.P.</creatorcontrib><creatorcontrib>Sankaran, P.G.</creatorcontrib><creatorcontrib>Dhanavanthan, P.</creatorcontrib><collection>CrossRef</collection><jtitle>Bulletin - Calcutta Statistical Association</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sreedevi, E.P.</au><au>Sankaran, P.G.</au><au>Dhanavanthan, P.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Nonparametric Test for Independence of Time to Failure and Cause of Failure of Current Status Competing Risks Data</atitle><jtitle>Bulletin - Calcutta Statistical Association</jtitle><date>2012-09</date><risdate>2012</risdate><volume>64</volume><issue>3-4</issue><spage>167</spage><epage>180</epage><pages>167-180</pages><issn>0008-0683</issn><eissn>2456-6462</eissn><abstract>Abtsrcat
Competing risks data are common in medical research in which lifetime of individuals can be classied in terms of causes of failure. Current status censoring occurs, if patients (objects) in a study are observed only once at a random monitoring time and only the information whether the event of interest has occurred or not prior to the monitoring time is available. Such data arise frequently from cross sectional studies in demography, epidemiology and reliability studies. In the present paper, we study current status data with competing risks. We develop a non parametric test for independence of time to failure and cause of failure of current status competing risks data. The asymptotic property of the test statistic is also discussed. Simulation studies and a real data example illustrate the practical utility of the procedure.</abstract><cop>New Delhi, India</cop><pub>SAGE Publications</pub><doi>10.1177/0008068320120302</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Bulletin - Calcutta Statistical Association, 2012-09, Vol.64 (3-4), p.167-180 |
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| title | A Nonparametric Test for Independence of Time to Failure and Cause of Failure of Current Status Competing Risks Data |
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