Asymptotic expansions and the reliability of tests in accelerated failure time models
This paper gives matrix formilae for the O(n -1 ) cerrecti0n applicable to asymptotically efficient conditional moment tests. These formulae only require expectations of functions involving, at most, second order derivatives of the log-likelihood; unlike those previously providcd by Ferrari and Cord...
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| Veröffentlicht in: | Journal of statistical computation and simulation 2000-01, Vol.65 (1-4), p.109-132 |
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| container_end_page | 132 |
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| container_title | Journal of statistical computation and simulation |
| container_volume | 65 |
| creator | Orme, Chris D. Peters, Simon A |
| description | This paper gives matrix formilae for the O(n
-1
) cerrecti0n applicable to asymptotically efficient conditional moment tests. These formulae only require expectations of functions involving, at most, second order derivatives of the log-likelihood; unlike those previously providcd by Ferrari and Corddro(1994). The correction is used to assess the reliability of first order asymptotic theory for arbitrary residual-based diagnostics in a class of accelerated failure time models: this correction is always parameter free, depending only on the number of included covariates in the regression design. For all but one of the tests considered, first order theory is found to be extremely unreliable, even in quite large samples, although this may not be widely appreciated by applied workers. |
| doi_str_mv | 10.1080/00949650008811993 |
| format | Article |
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-1
) cerrecti0n applicable to asymptotically efficient conditional moment tests. These formulae only require expectations of functions involving, at most, second order derivatives of the log-likelihood; unlike those previously providcd by Ferrari and Corddro(1994). The correction is used to assess the reliability of first order asymptotic theory for arbitrary residual-based diagnostics in a class of accelerated failure time models: this correction is always parameter free, depending only on the number of included covariates in the regression design. For all but one of the tests considered, first order theory is found to be extremely unreliable, even in quite large samples, although this may not be widely appreciated by applied workers.</description><identifier>ISSN: 0094-9655</identifier><identifier>EISSN: 1563-5163</identifier><identifier>DOI: 10.1080/00949650008811993</identifier><identifier>CODEN: JSCSAJ</identifier><language>eng</language><publisher>Abingdon: Gordon and Breach Science Publishers</publisher><subject>accelerated failure time models ; Asymptotic expansions ; conditional moment tests ; Distribution theory ; Exact sciences and technology ; Mathematics ; Parametric inference ; Probability and statistics ; Sciences and techniques of general use ; Statistics</subject><ispartof>Journal of statistical computation and simulation, 2000-01, Vol.65 (1-4), p.109-132</ispartof><rights>Copyright Taylor & Francis Group, LLC 2000</rights><rights>2000 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c373t-30f4db73efa92b5fe3cd7b1d93de377965971223374c355cc65cb9f66654fc553</citedby><cites>FETCH-LOGICAL-c373t-30f4db73efa92b5fe3cd7b1d93de377965971223374c355cc65cb9f66654fc553</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.tandfonline.com/doi/pdf/10.1080/00949650008811993$$EPDF$$P50$$Ginformaworld$$H</linktopdf><linktohtml>$$Uhttps://www.tandfonline.com/doi/full/10.1080/00949650008811993$$EHTML$$P50$$Ginformaworld$$H</linktohtml><link.rule.ids>314,776,780,4009,27902,27903,27904,59623,60412</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=1341705$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Orme, Chris D.</creatorcontrib><creatorcontrib>Peters, Simon A</creatorcontrib><title>Asymptotic expansions and the reliability of tests in accelerated failure time models</title><title>Journal of statistical computation and simulation</title><description>This paper gives matrix formilae for the O(n
-1
) cerrecti0n applicable to asymptotically efficient conditional moment tests. These formulae only require expectations of functions involving, at most, second order derivatives of the log-likelihood; unlike those previously providcd by Ferrari and Corddro(1994). The correction is used to assess the reliability of first order asymptotic theory for arbitrary residual-based diagnostics in a class of accelerated failure time models: this correction is always parameter free, depending only on the number of included covariates in the regression design. For all but one of the tests considered, first order theory is found to be extremely unreliable, even in quite large samples, although this may not be widely appreciated by applied workers.</description><subject>accelerated failure time models</subject><subject>Asymptotic expansions</subject><subject>conditional moment tests</subject><subject>Distribution theory</subject><subject>Exact sciences and technology</subject><subject>Mathematics</subject><subject>Parametric inference</subject><subject>Probability and statistics</subject><subject>Sciences and techniques of general use</subject><subject>Statistics</subject><issn>0094-9655</issn><issn>1563-5163</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2000</creationdate><recordtype>article</recordtype><recordid>eNqFkE1LAzEURYMoWKs_wF0WbkeTeZNJA25K0SoU3Nj1kMkHRjKTIYnY-fdOqeKiiKu3eOdcLheha0puKVmQO0JEJWpGCFksKBUCTtCMshoKRms4RbP9v5gAdo4uUnqfOEpZOUPbZRq7IYfsFDa7QfbJhT5h2Wuc3wyOxjvZOu_yiIPF2aScsOuxVMp4E2U2Glvp_Ec0OLvO4C5o49MlOrPSJ3P1fedo-_jwunoqNi_r59VyUyjgkAsgttItB2OlKFtmDSjNW6oFaAOcT3UFp2UJwCsFjClVM9UKW9c1q6xiDOaIHnJVDClFY5shuk7GsaGk2e_SHO0yOTcHZ5BJSW-j7JVLvyJUlJN9ND9grrchdvIzRK-bLEcf4o9zFN7kXZ7M-39N-LvfF_HuiGU</recordid><startdate>20000101</startdate><enddate>20000101</enddate><creator>Orme, Chris D.</creator><creator>Peters, Simon A</creator><general>Gordon and Breach Science Publishers</general><general>Taylor and Francis</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20000101</creationdate><title>Asymptotic expansions and the reliability of tests in accelerated failure time models</title><author>Orme, Chris D. ; Peters, Simon A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c373t-30f4db73efa92b5fe3cd7b1d93de377965971223374c355cc65cb9f66654fc553</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2000</creationdate><topic>accelerated failure time models</topic><topic>Asymptotic expansions</topic><topic>conditional moment tests</topic><topic>Distribution theory</topic><topic>Exact sciences and technology</topic><topic>Mathematics</topic><topic>Parametric inference</topic><topic>Probability and statistics</topic><topic>Sciences and techniques of general use</topic><topic>Statistics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Orme, Chris D.</creatorcontrib><creatorcontrib>Peters, Simon A</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><jtitle>Journal of statistical computation and simulation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Orme, Chris D.</au><au>Peters, Simon A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Asymptotic expansions and the reliability of tests in accelerated failure time models</atitle><jtitle>Journal of statistical computation and simulation</jtitle><date>2000-01-01</date><risdate>2000</risdate><volume>65</volume><issue>1-4</issue><spage>109</spage><epage>132</epage><pages>109-132</pages><issn>0094-9655</issn><eissn>1563-5163</eissn><coden>JSCSAJ</coden><abstract>This paper gives matrix formilae for the O(n
-1
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| issn | 0094-9655 1563-5163 |
| language | eng |
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| source | Taylor & Francis Journals Complete |
| subjects | accelerated failure time models Asymptotic expansions conditional moment tests Distribution theory Exact sciences and technology Mathematics Parametric inference Probability and statistics Sciences and techniques of general use Statistics |
| title | Asymptotic expansions and the reliability of tests in accelerated failure time models |
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