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Title: Spatial analysis of exposure coefficients with applications to stomach cancer
Author: Martinho, Maria
ISNI:       0000 0001 3620 349X
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2007
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Earlier ecological studies on the relation between H. pylori infection and stomach cancer have considered that the relation between these two variables, as estimated by the exposure coefficient, is constant. However, there is evidence to suggest that this relation changes geographically due to differences in strains of H. pylori. Since the prevalence of H. pylori varies with socio-economic status, the association between the latter and stomach cancer mortality may also vary geographically. This thesis studies stomach cancer by taking into account the geographical variability of the exposure coefficients. The study proposes the use of regression mixtures, clustering models and spatially varying regressions for the study of varying exposure coefficients. The effect of transformations of variables in these models appears to have been little considered. We provide new necessary conditions for invariance under transformations of variables for mixed effect models in general, and for the proposed models in particular. In addition, we show that varying exposure coefficients may induce a varying baseline risk. The regression mixtures and the clustering model are applied to a data set on stomach cancer incidence and H. pylori prevalence in 57 countries worldwide. We extend the clustering model to reflect any distance measure between the geographical units, including the Euclidean distance, in the formation of clusters. We also show that the clustering model performs better than the regression mixture model when the aim is to identify connected clusters and the observations present large variance. The results obtained with the clustering model supported the existence of three clusters where the interaction between the human and H. pylori populations have similar characteristics. Spatially varying regressions are applied to a data set of areal death counts of stomach cancer and spending power in 275 counties in continental Portugal. We provide an original strategy for implementing multivectorial intrinsic autoregressions as the distribution for the random effects. The results obtained with the application of this methodology were consistent with a varying exposure coefficient of spending power.
Supervisor: Bithell, John Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Statistics (social sciences) ; Health and health policy ; spatial analysis ; stomach cancer ; H. pylori ; regression mixtures ; clustering models ; spatially varying regressions ; varying exposure coefficients ; Portugal