Multilevel regression modelling of melanoma incidence

2.50
Hdl Handle:
http://hdl.handle.net/10547/265992
Title:
Multilevel regression modelling of melanoma incidence
Authors:
Brown, Antony Clark
Abstract:
This thesis is concerned with developing and implementing a method for modelling and projecting cancer incidence data. The burden of cancer is an increasing problem for society and therefore, the ability to analyse and predict trends in large scale populations is vital. These predictions based on incidence and mortality data collected by cancer registries, can be used for estimation of current and future rates, which is helpful for public health planning. A large body of work already exists on the use of various modelling strategies, methods and fitting techniques. A multilevel method of preparing the data is proposed, fitted to historical data using regression modelling, to predict future rates of incidence for a given population. The proposed model starts with a model for the total incidence of the population, with each successive level stratifying the data into progressively more specific groupings, based on age. Each grouping is partitioned into subgroups, and each subgroup is expressed as a proportion of the parent group. Models are fitted to each of the proportional age-groups, and a combination of these models produces a model that predicts incidence for a specific age. A simple, efficient implementation of the modelling procedure is described, including key algorithms and measures of performance. The method is applied to data from populations that have very different melanoma incidence (the USA and Australia). The proportional structure reveals that the proportional age trends present in both populations are remarkably similar, indicating that there are links between causative factors in both populations. The method is applied fully to data from a variety of populations, and compared with results from existing models. The method is shown to be able to produce results that are reliable and stable, and are generally significantly more accurate than those of other models.
Citation:
Brown, A.C. (2007) 'Multilevel regression modelling of melanoma incidence'. PhD Thesis. University of Bedfordshire.
Publisher:
University of Bedfordshire
Issue Date:
Dec-2007
URI:
http://hdl.handle.net/10547/265992
Type:
Thesis or dissertation
Language:
en
Description:
In partial fulfilment of the requirements for the degree of Doctor of Philosophy in the subject of Mathematics and Computer Science.
Appears in Collections:
PhD e-theses

Full metadata record

DC FieldValue Language
dc.contributor.authorBrown, Antony Clarken_GB
dc.date.accessioned2013-01-18T12:52:35Z-
dc.date.available2013-01-18T12:52:35Z-
dc.date.issued2007-12-
dc.identifier.citationBrown, A.C. (2007) 'Multilevel regression modelling of melanoma incidence'. PhD Thesis. University of Bedfordshire.en_GB
dc.identifier.urihttp://hdl.handle.net/10547/265992-
dc.descriptionIn partial fulfilment of the requirements for the degree of Doctor of Philosophy in the subject of Mathematics and Computer Science.en_GB
dc.description.abstractThis thesis is concerned with developing and implementing a method for modelling and projecting cancer incidence data. The burden of cancer is an increasing problem for society and therefore, the ability to analyse and predict trends in large scale populations is vital. These predictions based on incidence and mortality data collected by cancer registries, can be used for estimation of current and future rates, which is helpful for public health planning. A large body of work already exists on the use of various modelling strategies, methods and fitting techniques. A multilevel method of preparing the data is proposed, fitted to historical data using regression modelling, to predict future rates of incidence for a given population. The proposed model starts with a model for the total incidence of the population, with each successive level stratifying the data into progressively more specific groupings, based on age. Each grouping is partitioned into subgroups, and each subgroup is expressed as a proportion of the parent group. Models are fitted to each of the proportional age-groups, and a combination of these models produces a model that predicts incidence for a specific age. A simple, efficient implementation of the modelling procedure is described, including key algorithms and measures of performance. The method is applied to data from populations that have very different melanoma incidence (the USA and Australia). The proportional structure reveals that the proportional age trends present in both populations are remarkably similar, indicating that there are links between causative factors in both populations. The method is applied fully to data from a variety of populations, and compared with results from existing models. The method is shown to be able to produce results that are reliable and stable, and are generally significantly more accurate than those of other models.en_GB
dc.language.isoenen
dc.publisherUniversity of Bedfordshireen_GB
dc.subjectG340 Statistical Modellingen_GB
dc.subjectmelanomaen_GB
dc.subjectcanceren_GB
dc.subjectstatistical modellingen_GB
dc.subjectmodellingen_GB
dc.titleMultilevel regression modelling of melanoma incidenceen
dc.typeThesis or dissertationen
dc.type.qualificationnamePhDen
dc.type.qualificationlevelDoctoralen
dc.publisher.institutionUniversity of Bedfordshireen
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