Longitudinal models for polytomous responses
Recent work by Miller and Landis (1991) discusses generalized variance component models for polytomous responses. This work is adapted to longitudinal models for repeated measures of individuals having polytomous responses. In this setting, individuals are considered to be "clusters". The...
Gespeichert in:
| Veröffentlicht in: | Communications in statistics. Theory and methods 1993-01, Vol.22 (12), p.3523-3536 |
|---|---|
| 1. Verfasser: | |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 3536 |
|---|---|
| container_issue | 12 |
| container_start_page | 3523 |
| container_title | Communications in statistics. Theory and methods |
| container_volume | 22 |
| creator | Von Tress, Mark |
| description | Recent work by Miller and Landis (1991) discusses generalized variance component models for polytomous responses. This work is adapted to longitudinal models for repeated measures of individuals having polytomous responses. In this setting, individuals are considered to be "clusters". The resulting simplifications are discussed. First, each response has a multinomial distribution with N=l. Second, observed cluster proportions in the variance component estimates must be replaced by their expectations. This technique accommodates patients with missing data in a sequence of repeated observations. |
| doi_str_mv | 10.1080/03610929308831230 |
| format | Article |
| fullrecord | <record><control><sourceid>pascalfrancis_infor</sourceid><recordid>TN_cdi_pascalfrancis_primary_4103638</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>4103638</sourcerecordid><originalsourceid>FETCH-LOGICAL-c279t-1cc4595998553e3ed1ad5ee69274ed0ac0673dcf05184b8464579163f85824ba3</originalsourceid><addsrcrecordid>eNp1j01LxDAQQIMouK7-AG89eLQ600naBLzI4hcUvCh4K9kklUralKSL7L-3y6oX8TSHeW-Gx9g5whWChGugEkEVikBKwoLggC1QUJFzFG-HbLHb5zNQHrOTlD4AUFSSFuyyDsN7N21sN2if9cE6n7I2xGwMfjuFPmxSFl0aw5BcOmVHrfbJnX3PJXu9v3tZPeb188PT6rbOTVGpKUdjuFBCKSkEOXIWtRXOlaqouLOgDZQVWdOCQMnXkpdcVApLaqWQBV9rWjLc3zUxpBRd24yx63XcNgjNLrf5kzs7F3tn1Mlo30Y9mC79ihxnheSM3eyxbpgre_0ZorfNpLc-xB-H_v_yBXrdZk0</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Longitudinal models for polytomous responses</title><source>Taylor & Francis Journals Complete</source><creator>Von Tress, Mark</creator><creatorcontrib>Von Tress, Mark</creatorcontrib><description>Recent work by Miller and Landis (1991) discusses generalized variance component models for polytomous responses. This work is adapted to longitudinal models for repeated measures of individuals having polytomous responses. In this setting, individuals are considered to be "clusters". The resulting simplifications are discussed. First, each response has a multinomial distribution with N=l. Second, observed cluster proportions in the variance component estimates must be replaced by their expectations. This technique accommodates patients with missing data in a sequence of repeated observations.</description><identifier>ISSN: 0361-0926</identifier><identifier>EISSN: 1532-415X</identifier><identifier>DOI: 10.1080/03610929308831230</identifier><identifier>CODEN: CSTMDC</identifier><language>eng</language><publisher>Philadelphia, PA: Marcel Dekker, Inc</publisher><subject>Exact sciences and technology ; Gee ; Mathematics ; Multivariate analysis ; Probability and statistics ; repeated measures ; Sciences and techniques of general use ; Statistics</subject><ispartof>Communications in statistics. Theory and methods, 1993-01, Vol.22 (12), p.3523-3536</ispartof><rights>Copyright Taylor & Francis Group, LLC 1993</rights><rights>1994 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c279t-1cc4595998553e3ed1ad5ee69274ed0ac0673dcf05184b8464579163f85824ba3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.tandfonline.com/doi/pdf/10.1080/03610929308831230$$EPDF$$P50$$Ginformaworld$$H</linktopdf><linktohtml>$$Uhttps://www.tandfonline.com/doi/full/10.1080/03610929308831230$$EHTML$$P50$$Ginformaworld$$H</linktohtml><link.rule.ids>309,310,314,776,780,785,786,4036,4037,23909,23910,25118,27901,27902,59620,60409</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=4103638$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Von Tress, Mark</creatorcontrib><title>Longitudinal models for polytomous responses</title><title>Communications in statistics. Theory and methods</title><description>Recent work by Miller and Landis (1991) discusses generalized variance component models for polytomous responses. This work is adapted to longitudinal models for repeated measures of individuals having polytomous responses. In this setting, individuals are considered to be "clusters". The resulting simplifications are discussed. First, each response has a multinomial distribution with N=l. Second, observed cluster proportions in the variance component estimates must be replaced by their expectations. This technique accommodates patients with missing data in a sequence of repeated observations.</description><subject>Exact sciences and technology</subject><subject>Gee</subject><subject>Mathematics</subject><subject>Multivariate analysis</subject><subject>Probability and statistics</subject><subject>repeated measures</subject><subject>Sciences and techniques of general use</subject><subject>Statistics</subject><issn>0361-0926</issn><issn>1532-415X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1993</creationdate><recordtype>article</recordtype><recordid>eNp1j01LxDAQQIMouK7-AG89eLQ600naBLzI4hcUvCh4K9kklUralKSL7L-3y6oX8TSHeW-Gx9g5whWChGugEkEVikBKwoLggC1QUJFzFG-HbLHb5zNQHrOTlD4AUFSSFuyyDsN7N21sN2if9cE6n7I2xGwMfjuFPmxSFl0aw5BcOmVHrfbJnX3PJXu9v3tZPeb188PT6rbOTVGpKUdjuFBCKSkEOXIWtRXOlaqouLOgDZQVWdOCQMnXkpdcVApLaqWQBV9rWjLc3zUxpBRd24yx63XcNgjNLrf5kzs7F3tn1Mlo30Y9mC79ihxnheSM3eyxbpgre_0ZorfNpLc-xB-H_v_yBXrdZk0</recordid><startdate>19930101</startdate><enddate>19930101</enddate><creator>Von Tress, Mark</creator><general>Marcel Dekker, Inc</general><general>Taylor & Francis</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>19930101</creationdate><title>Longitudinal models for polytomous responses</title><author>Von Tress, Mark</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c279t-1cc4595998553e3ed1ad5ee69274ed0ac0673dcf05184b8464579163f85824ba3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1993</creationdate><topic>Exact sciences and technology</topic><topic>Gee</topic><topic>Mathematics</topic><topic>Multivariate analysis</topic><topic>Probability and statistics</topic><topic>repeated measures</topic><topic>Sciences and techniques of general use</topic><topic>Statistics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Von Tress, Mark</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><jtitle>Communications in statistics. Theory and methods</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Von Tress, Mark</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Longitudinal models for polytomous responses</atitle><jtitle>Communications in statistics. Theory and methods</jtitle><date>1993-01-01</date><risdate>1993</risdate><volume>22</volume><issue>12</issue><spage>3523</spage><epage>3536</epage><pages>3523-3536</pages><issn>0361-0926</issn><eissn>1532-415X</eissn><coden>CSTMDC</coden><abstract>Recent work by Miller and Landis (1991) discusses generalized variance component models for polytomous responses. This work is adapted to longitudinal models for repeated measures of individuals having polytomous responses. In this setting, individuals are considered to be "clusters". The resulting simplifications are discussed. First, each response has a multinomial distribution with N=l. Second, observed cluster proportions in the variance component estimates must be replaced by their expectations. This technique accommodates patients with missing data in a sequence of repeated observations.</abstract><cop>Philadelphia, PA</cop><pub>Marcel Dekker, Inc</pub><doi>10.1080/03610929308831230</doi><tpages>14</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0361-0926 |
| ispartof | Communications in statistics. Theory and methods, 1993-01, Vol.22 (12), p.3523-3536 |
| issn | 0361-0926 1532-415X |
| language | eng |
| recordid | cdi_pascalfrancis_primary_4103638 |
| source | Taylor & Francis Journals Complete |
| subjects | Exact sciences and technology Gee Mathematics Multivariate analysis Probability and statistics repeated measures Sciences and techniques of general use Statistics |
| title | Longitudinal models for polytomous responses |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-06T11%3A58%3A59IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-pascalfrancis_infor&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Longitudinal%20models%20for%20polytomous%20responses&rft.jtitle=Communications%20in%20statistics.%20Theory%20and%20methods&rft.au=Von%20Tress,%20Mark&rft.date=1993-01-01&rft.volume=22&rft.issue=12&rft.spage=3523&rft.epage=3536&rft.pages=3523-3536&rft.issn=0361-0926&rft.eissn=1532-415X&rft.coden=CSTMDC&rft_id=info:doi/10.1080/03610929308831230&rft_dat=%3Cpascalfrancis_infor%3E4103638%3C/pascalfrancis_infor%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |