Random coeffcient models for complex longitudinal data
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| Title: | Random coeffcient models for complex longitudinal data |
|---|---|
| Authors: | Kidney, Darren |
| Committee Members: | Donovan, Carl Robert; MacKenzie, Monique Lea |
| Summary: | Longitudinal data are common in biological research. However, real data sets vary considerably in terms of their structure and complexity and present many challenges for statistical modelling. This thesis proposes a series of methods using random coefficients for modelling two broad types of longitudinal response: normally distributed measurements and binary recapture data. Biased inference can occur in linear mixed-effects modelling if subjects are drawn from a number of unknown sub-populations, or if the residual covariance is poorly specified. To address some of the shortcomings of previous approaches in terms of model selection and flexibility, this thesis presents methods for: (i) determining the presence of latent grouping structures using a two-step approach, involving regression splines for modelling functional random effects and mixture modelling of the fitted random effects; and (ii) flexible of modelling of the residual covariance matrix using regression splines to specify smooth and potentially non-monotonic variance and correlation functions. Spatially explicit capture-recapture methods for estimating the density of animal populations have shown a rapid increase in popularity over recent years. However, further refinements to existing theory and fitting software are required to apply these methods in many situations. This thesis presents: (i) an analysis of recapture data from an acoustic survey of gibbons using supplementary data in the form of estimated angles to detections, (ii) the development of a multi-occasion likelihood including a model for stochastic availability using a partially observed random effect (interpreted in terms of calling behaviour in the case of gibbons), and (iii) an analysis of recapture data from a population of radio-tagged skates using a conditional likelihood that allows the density of animal activity centres to be modelled as functions of time, space and animal-level covariates. |
| URL: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.644817 |
| Database: | OpenDissertations |
| FullText | Text: Availability: 0 |
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| Header | DbId: ddu DbLabel: OpenDissertations An: ddu.oai.ethos.bl.uk.644817 AccessLevel: 6 PubType: Dissertation/ Thesis PubTypeId: dissertation PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Random coeffcient models for complex longitudinal data – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Kidney%2C+Darren%22">Kidney, Darren</searchLink> – Name: Author Label: Committee Members Group: Au Data: <searchLink fieldCode="CO" term="%22Donovan%2C+Carl+Robert%22">Donovan, Carl Robert</searchLink>; <searchLink fieldCode="CO" term="%22MacKenzie%2C+Monique+Lea%22">MacKenzie, Monique Lea</searchLink> – Name: Abstract Label: Summary Group: Ab Data: Longitudinal data are common in biological research. However, real data sets vary considerably in terms of their structure and complexity and present many challenges for statistical modelling. This thesis proposes a series of methods using random coefficients for modelling two broad types of longitudinal response: normally distributed measurements and binary recapture data. Biased inference can occur in linear mixed-effects modelling if subjects are drawn from a number of unknown sub-populations, or if the residual covariance is poorly specified. To address some of the shortcomings of previous approaches in terms of model selection and flexibility, this thesis presents methods for: (i) determining the presence of latent grouping structures using a two-step approach, involving regression splines for modelling functional random effects and mixture modelling of the fitted random effects; and (ii) flexible of modelling of the residual covariance matrix using regression splines to specify smooth and potentially non-monotonic variance and correlation functions. Spatially explicit capture-recapture methods for estimating the density of animal populations have shown a rapid increase in popularity over recent years. However, further refinements to existing theory and fitting software are required to apply these methods in many situations. This thesis presents: (i) an analysis of recapture data from an acoustic survey of gibbons using supplementary data in the form of estimated angles to detections, (ii) the development of a multi-occasion likelihood including a model for stochastic availability using a partially observed random effect (interpreted in terms of calling behaviour in the case of gibbons), and (iii) an analysis of recapture data from a population of radio-tagged skates using a conditional likelihood that allows the density of animal activity centres to be modelled as functions of time, space and animal-level covariates. – Name: URL Label: URL Group: URL Data: <link linkTarget="URL" linkTerm="http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.644817" linkWindow="_blank">http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.644817</link> |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ddu&AN=ddu.oai.ethos.bl.uk.644817 |
| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English Subjects: – SubjectFull: 519.5 Type: general – SubjectFull: Random effects ; Mixed effects models ; Autocorrelation ; Spatially explicit capture-recapture ; SECR ; Availability ; QA278.K53 ; Multilevel models (Statistics) ; Autocorrelation (Statistics) Type: general Titles: – TitleFull: Random coeffcient models for complex longitudinal data Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kidney, Darren IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2014 |
| ResultId | 1 |
