Discrete-time event history analysis using segmented hazards
Event history analysis is a means of explaining variation in the timing of events in individual life histories. This article describes methods for overcoming two difficult problems likely to be encountered in applications of event history analysis to studies of aging and human development. First, in...
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| Veröffentlicht in: | Experimental aging research 1991-12, Vol.17 (4), p.251-260 |
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| container_title | Experimental aging research |
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| creator | Gardner, William Meyer, Marion Ketterlinus, Robert |
| description | Event history analysis is a means of explaining variation in the timing of events in individual life histories. This article describes methods for overcoming two difficult problems likely to be encountered in applications of event history analysis to studies of aging and human development. First, in many studies the ages of occurrence of critical life events are recorded in discrete units such as years, but the probability distributions of life events are usually specified in continuous-time form. We show how to estimate models for discrete-time data based on an underlying continuous-time specification. Second, the standard distributions for life events often fail to capture the complex age-dependence seen in actual data. We show how to construct a model using segmented hazards, that is, a composite of different functions for different segments of time. To illustrate these points, we study the age of first intercourse of 11,883 subjects from the National Longitudinal Study of Youth. |
| doi_str_mv | 10.1080/03610739108253902 |
| format | Article |
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To illustrate these points, we study the age of first intercourse of 11,883 subjects from the National Longitudinal Study of Youth.</description><identifier>ISSN: 0361-073X</identifier><identifier>EISSN: 1096-4657</identifier><identifier>DOI: 10.1080/03610739108253902</identifier><identifier>PMID: 1820290</identifier><language>eng</language><publisher>United States: Taylor & Francis Group</publisher><subject>Adolescent ; Adult ; Age Factors ; Aged ; Aged, 80 and over ; Child ; Child, Preschool ; Computer Simulation ; Female ; Humans ; Infant ; Infant, Newborn ; Life Change Events ; Longitudinal Studies ; Male ; Middle Aged ; Models, Statistical ; Proportional Hazards Models ; Time</subject><ispartof>Experimental aging research, 1991-12, Vol.17 (4), p.251-260</ispartof><rights>Copyright Taylor & Francis Group, LLC 1991</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c301t-5a8c87017bbeaaaea34c2a7385da134a177c262ab9d57e362445ee11a64052783</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.tandfonline.com/doi/pdf/10.1080/03610739108253902$$EPDF$$P50$$Ginformaworld$$H</linktopdf><linktohtml>$$Uhttps://www.tandfonline.com/doi/full/10.1080/03610739108253902$$EHTML$$P50$$Ginformaworld$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,59624,60413</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/1820290$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gardner, William</creatorcontrib><creatorcontrib>Meyer, Marion</creatorcontrib><creatorcontrib>Ketterlinus, Robert</creatorcontrib><title>Discrete-time event history analysis using segmented hazards</title><title>Experimental aging research</title><addtitle>Exp Aging Res</addtitle><description>Event history analysis is a means of explaining variation in the timing of events in individual life histories. 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To illustrate these points, we study the age of first intercourse of 11,883 subjects from the National Longitudinal Study of Youth.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Age Factors</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Computer Simulation</subject><subject>Female</subject><subject>Humans</subject><subject>Infant</subject><subject>Infant, Newborn</subject><subject>Life Change Events</subject><subject>Longitudinal Studies</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Models, Statistical</subject><subject>Proportional Hazards Models</subject><subject>Time</subject><issn>0361-073X</issn><issn>1096-4657</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1991</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kEtLw0AUhQdRaq3-ABdCVu6id16ZBLqR-oSCGwV3w01y00byqDOpEn-9KSm4EFeXw3fO4XIYO-dwxSGGa5ARByOTQQgtExAHbMohiUIVaXPIpjseDoa3Y3bi_TsAaMnlhE14LEAkMGXz29JnjjoKu7KmgD6p6YJ16bvW9QE2WPW-9MHWl80q8LSqB0x5sMZvdLk_ZUcFVp7O9nfGXu_vXhaP4fL54WlxswwzCbwLNcZZbICbNCVEJJQqE2hkrHPkUiE3JhORwDTJtSEZCaU0EecYKdDCxHLGLsfejWs_tuQ7Ww9fU1VhQ-3WWyOMMlyZwchHY-Za7x0VduPKGl1vOdjdYvbPYkPmYl--TWvKfxPjRAOfj7xsitbV-NW6Krcd9lXrCodNVnor_6__AaL6eEg</recordid><startdate>19911201</startdate><enddate>19911201</enddate><creator>Gardner, William</creator><creator>Meyer, Marion</creator><creator>Ketterlinus, Robert</creator><general>Taylor & Francis Group</general><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>7X8</scope></search><sort><creationdate>19911201</creationdate><title>Discrete-time event history analysis using segmented hazards</title><author>Gardner, William ; Meyer, Marion ; Ketterlinus, Robert</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c301t-5a8c87017bbeaaaea34c2a7385da134a177c262ab9d57e362445ee11a64052783</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1991</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Age Factors</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Child</topic><topic>Child, Preschool</topic><topic>Computer Simulation</topic><topic>Female</topic><topic>Humans</topic><topic>Infant</topic><topic>Infant, Newborn</topic><topic>Life Change Events</topic><topic>Longitudinal Studies</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Models, Statistical</topic><topic>Proportional Hazards Models</topic><topic>Time</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gardner, William</creatorcontrib><creatorcontrib>Meyer, Marion</creatorcontrib><creatorcontrib>Ketterlinus, Robert</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Experimental aging research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gardner, William</au><au>Meyer, Marion</au><au>Ketterlinus, Robert</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Discrete-time event history analysis using segmented hazards</atitle><jtitle>Experimental aging research</jtitle><addtitle>Exp Aging Res</addtitle><date>1991-12-01</date><risdate>1991</risdate><volume>17</volume><issue>4</issue><spage>251</spage><epage>260</epage><pages>251-260</pages><issn>0361-073X</issn><eissn>1096-4657</eissn><abstract>Event history analysis is a means of explaining variation in the timing of events in individual life histories. 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| ispartof | Experimental aging research, 1991-12, Vol.17 (4), p.251-260 |
| issn | 0361-073X 1096-4657 |
| language | eng |
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| source | MEDLINE; Taylor & Francis Journals Complete |
| subjects | Adolescent Adult Age Factors Aged Aged, 80 and over Child Child, Preschool Computer Simulation Female Humans Infant Infant, Newborn Life Change Events Longitudinal Studies Male Middle Aged Models, Statistical Proportional Hazards Models Time |
| title | Discrete-time event history analysis using segmented hazards |
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