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Extended Hazard Regression for Censored Survival Data with Covariates: A Spline Approximation for the Baseline Hazard Function
A regression model for censored survival data with covariates is introduced and termed extended hazard regression (EHR). EHR includes the proportional hazards (PH) and the accelerated failure time (AFT) models as special cases. By approximating the baseline hazard function with quadratic splines, we...
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Published in: | Biometrics 1987-03, Vol.43 (1), p.181-192 |
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Language: | English |
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container_issue | 1 |
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container_title | Biometrics |
container_volume | 43 |
creator | Etezadi-Amoli, Jamshid Ciampi, Antonio |
description | A regression model for censored survival data with covariates is introduced and termed extended hazard regression (EHR). EHR includes the proportional hazards (PH) and the accelerated failure time (AFT) models as special cases. By approximating the baseline hazard function with quadratic splines, we develop a maximum likelihood estimation procedure to provide a simultaneous estimate of both the hazard function and the regression coefficients. The AFT and PH assumptions can then be compared by likelihood ratio tests within the more general EHR model. Several examples based on artificial and real data are discussed. |
doi_str_mv | 10.2307/2531958 |
format | article |
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Several examples based on artificial and real data are discussed.</description><subject>Approximation</subject><subject>Biological and medical sciences</subject><subject>Biometrics</subject><subject>Censored data</subject><subject>Computerized, statistical medical data processing and models in biomedicine</subject><subject>Datasets</subject><subject>Inference</subject><subject>Mathematical independent variables</subject><subject>Maximum likelihood estimation</subject><subject>Maximum likelihood estimators</subject><subject>Medical sciences</subject><subject>Medical statistics</subject><subject>Polynomials</subject><subject>Regression analysis</subject><issn>0006-341X</issn><issn>1541-0420</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1987</creationdate><recordtype>article</recordtype><recordid>eNp1kEtLw0AUhQdRsFbxL8xCcBWdRyYPdzW2VigIVsFdmExubErMhJlprC787U5t1ZWry-V8nHvPQeiUkgvGSXzJBKepSPbQgIqQBiRkZB8NCCFRwEP6fIiOrF36NRWEDdDneO2gLaHEU_khTYkf4MWAtbVucaUNzqC12nh5vjJ93csG30gn8VvtFjjTvTS1dGCv8AjPu6ZuAY-6zuh1_Srdj4VbAL6WFr7l3ZXJqlUb4BgdVLKxcLKbQ_Q0GT9m02B2f3uXjWaBomnkAloyzhMAxSkFn06yhEKVpFABEUyIpIgjH7AgolAF0DBKvcAUq1SYFLyI-RCdb32V0dYaqPLO-B_Ne05Jvqkt39XmybMt2UmrZFMZ2ara_uKxP0bS6A9bWqfNv25fG3Z4dQ</recordid><startdate>19870301</startdate><enddate>19870301</enddate><creator>Etezadi-Amoli, Jamshid</creator><creator>Ciampi, Antonio</creator><general>Biometric Society</general><general>Blackwell</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>19870301</creationdate><title>Extended Hazard Regression for Censored Survival Data with Covariates: A Spline Approximation for the Baseline Hazard Function</title><author>Etezadi-Amoli, Jamshid ; Ciampi, Antonio</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c196t-1d2338eec311e195a281ef89efe052558b76006b05bcbe1469fe02c2fc48b3b73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1987</creationdate><topic>Approximation</topic><topic>Biological and medical sciences</topic><topic>Biometrics</topic><topic>Censored data</topic><topic>Computerized, statistical medical data processing and models in biomedicine</topic><topic>Datasets</topic><topic>Inference</topic><topic>Mathematical independent variables</topic><topic>Maximum likelihood estimation</topic><topic>Maximum likelihood estimators</topic><topic>Medical sciences</topic><topic>Medical statistics</topic><topic>Polynomials</topic><topic>Regression analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Etezadi-Amoli, Jamshid</creatorcontrib><creatorcontrib>Ciampi, Antonio</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><jtitle>Biometrics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Etezadi-Amoli, Jamshid</au><au>Ciampi, Antonio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Extended Hazard Regression for Censored Survival Data with Covariates: A Spline Approximation for the Baseline Hazard Function</atitle><jtitle>Biometrics</jtitle><date>1987-03-01</date><risdate>1987</risdate><volume>43</volume><issue>1</issue><spage>181</spage><epage>192</epage><pages>181-192</pages><issn>0006-341X</issn><eissn>1541-0420</eissn><coden>BIOMA5</coden><abstract>A regression model for censored survival data with covariates is introduced and termed extended hazard regression (EHR). EHR includes the proportional hazards (PH) and the accelerated failure time (AFT) models as special cases. By approximating the baseline hazard function with quadratic splines, we develop a maximum likelihood estimation procedure to provide a simultaneous estimate of both the hazard function and the regression coefficients. The AFT and PH assumptions can then be compared by likelihood ratio tests within the more general EHR model. Several examples based on artificial and real data are discussed.</abstract><cop>Malden, MA</cop><pub>Biometric Society</pub><doi>10.2307/2531958</doi><tpages>12</tpages></addata></record> |
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language | eng |
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source | JSTOR Archival Journals and Primary Sources Collection |
subjects | Approximation Biological and medical sciences Biometrics Censored data Computerized, statistical medical data processing and models in biomedicine Datasets Inference Mathematical independent variables Maximum likelihood estimation Maximum likelihood estimators Medical sciences Medical statistics Polynomials Regression analysis |
title | Extended Hazard Regression for Censored Survival Data with Covariates: A Spline Approximation for the Baseline Hazard Function |
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