Markov Models for Repeated Ordinal Data
Objectives: To demonstrate the application of Markov models, especially for ordinal outcomes, within the context of regression models for correlated data. Methods: A brief review of regression methods for correlated data is given. A proportional odds model and a continuation ratio model is applied t...
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| Veröffentlicht in: | Methods of information in medicine 2006-01, Vol.45 (4), p.414-418 |
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| creator | Wellmann, J. |
| description | Objectives: To demonstrate the application of Markov models, especially for ordinal outcomes, within the context of regression models for correlated data. Methods: A brief review of regression methods for correlated data is given. A proportional odds model and a continuation ratio model is applied to repeated measurements of macular pigment density, obtained in an intervention study on the supplementation of macular carotenoids. The correlation between repeated assessments is assumed to follow a first-order Markov model. The models are implemented with standard statistical software. Results: Both models, though not directly comparable, provide a similar conclusion. The application of these models with standard statistical software is straightforward. Conclusions: Markov models can be valuable alternatives to random effects modes or procedures based on generalized estimation equations. |
| doi_str_mv | 10.1055/s-0038-1634097 |
| format | Article |
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Methods: A brief review of regression methods for correlated data is given. A proportional odds model and a continuation ratio model is applied to repeated measurements of macular pigment density, obtained in an intervention study on the supplementation of macular carotenoids. The correlation between repeated assessments is assumed to follow a first-order Markov model. The models are implemented with standard statistical software. Results: Both models, though not directly comparable, provide a similar conclusion. The application of these models with standard statistical software is straightforward. Conclusions: Markov models can be valuable alternatives to random effects modes or procedures based on generalized estimation equations.</description><identifier>ISSN: 0026-1270</identifier><identifier>EISSN: 2511-705X</identifier><identifier>DOI: 10.1055/s-0038-1634097</identifier><identifier>PMID: 16964358</identifier><language>eng</language><publisher>Germany: Schattauer Verlag für Medizin und Naturwissenschaften</publisher><subject>Carotenoids - administration & dosage ; Carotenoids - analysis ; continuation ratio model ; Dietary Supplements ; Disease Progression ; Generalized Estimation Equations ; Humans ; Logistic Models ; Longitudinal Studies ; Macular Degeneration - pathology ; Macular Degeneration - prevention & control ; Markov Chains ; Markov model ; Ophthalmology - statistics & numerical data ; Original Article ; Outcome Assessment (Health Care) - methods ; Proportional Hazards Models ; proportional odds model ; random effects ; Retinal Pigments - chemistry ; Software ; Time Factors</subject><ispartof>Methods of information in medicine, 2006-01, Vol.45 (4), p.414-418</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.thieme-connect.de/products/ejournals/pdf/10.1055/s-0038-1634097.pdf$$EPDF$$P50$$Gthieme$$H</linktopdf><linktohtml>$$Uhttps://www.thieme-connect.de/products/ejournals/html/10.1055/s-0038-1634097$$EHTML$$P50$$Gthieme$$H</linktohtml><link.rule.ids>314,776,780,3004,3005,27901,27902,54534,54535</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/16964358$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wellmann, J.</creatorcontrib><title>Markov Models for Repeated Ordinal Data</title><title>Methods of information in medicine</title><addtitle>Methods Inf Med</addtitle><description>Objectives: To demonstrate the application of Markov models, especially for ordinal outcomes, within the context of regression models for correlated data. Methods: A brief review of regression methods for correlated data is given. A proportional odds model and a continuation ratio model is applied to repeated measurements of macular pigment density, obtained in an intervention study on the supplementation of macular carotenoids. The correlation between repeated assessments is assumed to follow a first-order Markov model. The models are implemented with standard statistical software. Results: Both models, though not directly comparable, provide a similar conclusion. The application of these models with standard statistical software is straightforward. 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Methods: A brief review of regression methods for correlated data is given. A proportional odds model and a continuation ratio model is applied to repeated measurements of macular pigment density, obtained in an intervention study on the supplementation of macular carotenoids. The correlation between repeated assessments is assumed to follow a first-order Markov model. The models are implemented with standard statistical software. Results: Both models, though not directly comparable, provide a similar conclusion. The application of these models with standard statistical software is straightforward. Conclusions: Markov models can be valuable alternatives to random effects modes or procedures based on generalized estimation equations.</abstract><cop>Germany</cop><pub>Schattauer Verlag für Medizin und Naturwissenschaften</pub><pmid>16964358</pmid><doi>10.1055/s-0038-1634097</doi><tpages>5</tpages></addata></record> |
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| ispartof | Methods of information in medicine, 2006-01, Vol.45 (4), p.414-418 |
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| source | MEDLINE; Thieme Connect Journals |
| subjects | Carotenoids - administration & dosage Carotenoids - analysis continuation ratio model Dietary Supplements Disease Progression Generalized Estimation Equations Humans Logistic Models Longitudinal Studies Macular Degeneration - pathology Macular Degeneration - prevention & control Markov Chains Markov model Ophthalmology - statistics & numerical data Original Article Outcome Assessment (Health Care) - methods Proportional Hazards Models proportional odds model random effects Retinal Pigments - chemistry Software Time Factors |
| title | Markov Models for Repeated Ordinal Data |
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