Surface pasting is an interactive hierarchical modelling technique used to construct surfaces with varying levels of local detail. The concept is similar to that of the physical process of modelling with clay, where features are placed on to a base surface and attached by a smooth join obtained by adjusting the feature. Cylindrical surface pasting extends this modelling paradigm by allowing for two base surfaces to be joined smoothly via a blending cylinder, as in attaching a clay head to the body using a neck. Unfortunately, computer-based pasting involves approximations that can cause cracks to appear in the composite surface. In particular this occurs when the pasted feature boundary does not lie exactly over the user-specified pasting region on the base surface. Determining pasted locations for the feature boundary control points that give a close to exact join is non-trivial, especially in the case of cylinders as their control points can not be defined to lie on their closed curve boundary. I propose and compare six simple methods for positioning a feature cylinder's control points such that the join boundary discontinuities are minimized. The methods considered are all algorithmically simple alternatives having low computational costs. While the results demonstrate an order of magnitude quality improvement for some methods on a convex-only curved base, as the complexity of the base surface increases, all the methods show similar performance. Although unexpected, it turns out that a simple mapping of the control points directly onto the pasting closed curve given on the base surface offers a reasonable cylindrical boundary pasting technique.

Surface pasting is an interactive hierarchical modelling technique used to construct surfaces with varying levels of local detail. The concept is similar to that of the physical process of modelling with clay, where features are placed on to a base surface and attached by a smooth join obtained by adjusting the feature. Cylindrical surface pasting extends this modelling paradigm by allowing for two base surfaces to be joined smoothly via a blending cylinder, as in attaching a clay head to the body using a neck. Unfortunately, computer-based pasting involves approximations that can cause cracks to appear in the composite surface. In particular this occurs when the pasted feature boundary does not lie exactly over the user-specified pasting region on the base surface. Determining pasted locations for the feature boundary control points that give a close to exact join is non-trivial, especially in the case of cylinders as their control points can not be defined to lie on their closed curve boundary. I propose and compare six simple methods for positioning a feature cylinder's control points such that the join boundary discontinuities are minimized. The methods considered are all algorithmically simple alternatives having low computational costs. While the results demonstrate an order of magnitude quality improvement for some methods on a convex-only curved base, as the complexity of the base surface increases, all the methods show similar performance. Although unexpected, it turns out that a simple mapping of the control points directly onto the pasting closed curve given on the base surface offers a reasonable cylindrical boundary pasting technique.

This thesis consists of four individual essays and an introduction chapter. The essays are in the field of multilevel analysis of economic data. The first essay estimates capitalisation effects of farm attributes, with a particular focus on single farm payments (SFP), into the price of farms. Using a sample of Swedish farm transactions sold all across the country, the results from a spatial multiple-membership model suggests that the local effect of SFP is negative while there is a positive between-region effect of SFP, on farm prices.   The second essay investigates the extent to which differences in the probability to exit from part-time unemployment to a full-time job can be accounted for by spatial contextual factors and individual characteristics. To correctly incorporate contextual effects, a multilevel analysis was applied to explore whether contextual factors account for differences in the probability of transition to full-time employment between individuals with different characteristics. The results indicate that there is a contextual effect and that there are some spatial spill-over effects from neighbouring municipalities.   The third essay investigates the determinants of educational attainment for third-generation immigrants and natives in Sweden. Using a mixed-effects model that includes unobserved family heterogeneity, for linked register data, the main result is that the effect of parent’s educational attainment is mainly due to the between-parental education effect of family income.   The fourth and last essay presents a new robust strategy for performance evaluation in the case of panel data that is based on routinely collected variables or indicators. The suggested strategy applies a cross-classified, mixed-effect model. The strategy is implemented in two illustrative empirical examples, and the robustness is investigated in a Monte Carlo study.

Background: Transferring cost-effectiveness information between geographic domains offers the potential for more efficient use of analytical resources. However, it is difficult for decision-makers to know when they can rely on costeffectiveness evidence produced for another context. Objectives: This thesis explores the transferability of economic evaluation results produced for one geographic area to another location of interest, and develops an approach to identify factors to predict when this is appropriate. Methods: Multilevel statistical models were developed for the integration of published international costeffectiveness data to assess the impact of contextual effects on country-level; whilst controlling for baseline characteristics within, and across, a set of economic evaluation studies. Explanatory variables were derived from a list of factors suggested in the literature as possible constraints on the transferability of costeffectiveness evidence. The approach was illustrated using published estimates of the cost-effectiveness of statins for the primary and secondary prevention of cardiovascular disease from 67 studies and related to 23 geographic domains, together with covariates on data, study and country-level. Results: The proportion of variation at the country-level observed depends on the appropriate multilevel model structure and never exceeds 15% for incremental effects and 21% for incremental cost. Key sources of variability are patient and disease characteristics, intervention cost and a number of methodological characteristics defined on the data-level. There were fewer significant covariates on the study and country-levels. Conclusions: Analysis suggests that variability in cost-effectiveness data is primarily due to differences between studies, not countries. Further, comparing different models suggests that data from multinational studies severely underestimates country-level variability. Additional research is needed to test the robustness of these conclusions on other sets of cost-effectiveness data, to further explore the appropriate set of covariates, and to foster the development of multilevel statistical modelling for economic evaluation data in health.

Ferrets are amusing, flexible creatures that have been under represented in computer models. Because their bodies can assume almost any curved shape, splines are the natural tool for modelling ferrets. Surface pasting is a hierarchical method of modelling with spline surfaces, where features are added onto a base surface. Existing surface pasting techniques are limited to modelling rectilinear shapes. Using the task of modelling a ferret as a driving force, I propose a method of pasting cylinders in world space; I looked at methods for reducing distortion of pasted features; and I created a method for pasting trimmed features to allow for features that do not have the rectilinear shape of standard pasting. With my methods, modelling ferrets with surface pasting is easier, and the resulting models are closer to a real ferret.

Ferrets are amusing, flexible creatures that have been under represented in computer models. Because their bodies can assume almost any curved shape, splines are the natural tool for modelling ferrets. Surface pasting is a hierarchical method of modelling with spline surfaces, where features are added onto a base surface. Existing surface pasting techniques are limited to modelling rectilinear shapes. Using the task of modelling a ferret as a driving force, I propose a method of pasting cylinders in world space; I looked at methods for reducing distortion of pasted features; and I created a method for pasting trimmed features to allow for features that do not have the rectilinear shape of standard pasting. With my methods, modelling ferrets with surface pasting is easier, and the resulting models are closer to a real ferret.

To further support and optimise the production of diving tables for the Armed Forces of Sweden, a research team has developed a new machine called IGUM (Inert Gas UndersökningsMaskin) which aims to measure how inert gas is taken up and exhaled. Due to the new design of machine, the goal of this thesis was to statistically validate its accuracy and verify its reliability.  In the first stage, a quality assurance of the linear position conversion key of IGUM in a steady and known gas flow was conducted. This was done by collecting and analysing data in 29 experiments followed by examination with ordinary least squares, hypothesis testing, analysis of variance, bootstrapping and Bayesian hierarchical modelling. Autocorrelation among the residuals were detected but concluded to not have an impact on the results due to the bootstrap analysis. The results showed an estimated conversion key equal to 1.276 ml/linear position which was statistically significant for all 29 experiments.  In the second stage, it was examined if and how well IGUM could detect small additions of gas in a dynamic flow. The breathing machine ANSTI was used to simulate the sinus pattern of a breathing human in 24 experiments where 3 additions of 30 ml of gas manually was added into the system. The results were analysed through sinusoidal regression where three dummy variables represented the three additions of gas in each experiment. To examine if IGUM detects 30 ml for each input, the previously statistically proven conversion key at 1.276ml/linear position was used. An attempt was made to remove the seasonal trend in the data, something that was not completely successful which could influence the estimations. The results showed that IGUM indeed can detect these small gas additions, where the amount detected showed some differences between dummies and experiments. This is most likely since not enough trend has been removed, rather than IGUM not working properly.

In this dissertation, we study the stationary heat equation in a heterogeneous tridimensional plate, using a "dimension reduction" techinique called hierarchical modelling and we generate model the original problem in a two-dimensional domain. To estimate the error modelling, we develop an asymptotic expansion for the original problem solution and for the aproximate solution. Comparing both solutions with their own asymptotic expansions, we obtain an estimative of the error modelling. We perform some computational experiments, using the Residual Free Bubbles (RFB) Method and the Multiscale Finite Element Method for the diffusion problem and for the diffusion-reaction problem in a two-dimensional domain, with small parameters. Finally, we extend the numeric solutions found the original tridimensional problem. / Neste trabalho, estudamos a equação do calor estacionária em uma placa heterogênea tridimensional. Para a modelagem deste problema, utilizamos uma técnica de redução de dimensão conhecida por Modelagem Hierárquica. Desta forma, geramos um modelo para o problema original em um domínio bidimensional. Com o objetivo de estimar o erro de modelagem, desenvolvemos a expansão assintótica da solução do problema original e da solução aproximada. Comparando as soluções com suas respectivas expansões assintóticas, obtemos uma estimativa para o erro de modelagem. Realizamos alguns experimentos computacionais, desenvolvendo o método Residual Free Bubbles (RFB) e o método de Elementos Finitos Multiescala (MEFM) para o problema de difusão e para o problema de difusão-reação em um domínio bidimensional, com parâmetros pequenos. Com base nestes experimentos, encontramos algumas soluções numéricas para o problema da placa tridimensional.

Dissertação(mestrado) - Universidade Federal do Rio Grande, Programa de Pós–Graduação em Oceanografia Biológica, Instituto de Oceanografia, 2013. / Submitted by Cristiane Gomides (cristiane_gomides@hotmail.com) on 2013-10-09T18:43:46Z No. of bitstreams: 1 Heloise.pdf: 1525937 bytes, checksum: 44441e69ced9544eaba26ec6b8f8e2d9 (MD5) / Approved for entry into archive by Sabrina Andrade (sabrinabeatriz@ibest.com.br) on 2013-10-17T03:12:06Z (GMT) No. of bitstreams: 1 Heloise.pdf: 1525937 bytes, checksum: 44441e69ced9544eaba26ec6b8f8e2d9 (MD5) / Made available in DSpace on 2013-10-17T03:12:06Z (GMT). No. of bitstreams: 1 Heloise.pdf: 1525937 bytes, checksum: 44441e69ced9544eaba26ec6b8f8e2d9 (MD5) Previous issue date: 2013 / População é a unidade fundamental da conservação e sua forma mais simples de monitoramento envolve a amostragem temporal regular para a determinação do status populacional. Uma das populações de baleia jubarte do Hemisfério Sul utiliza a costa do Brasil entre maio e dezembro para se reprodução e criação dos filhotes. Esta população, denominada “estoque reprodutivo A” pela Comissão Internacional da Baleia, tem mostrado sinais de recuperação após um marcado declínio devido a caça e um longo período de moratória. Esta população se concentra principalmente no Banco dos Abrolhos (BA), onde águas calmas e quentes parecem constituir um hábitat ideal. Este estudo teve o objetivo de estimar o tamanho da população de jubartes para o ano de 2011, bem como predizer a distribuição de grupos na costa brasileira. O método de amostragem de distâncias foi implementado, e modelos hierárquicos Bayesianos foram propostos para estimar a abundância. Modelos auto-regressivos condicionais foram aplicados para predizer a densidade em células de 0.5° de latitude e longitude. O tamanho da população foi estimado em 10,160 baleias (Cr.I.95%=6,607-17,692). As maiores densidades foram encontradas entre o Banco dos Abrolhos e a Baía de Todos os Santos (BA). Os resultados sugerem que o aumento populacional acarreta a expansão da população para além do Banco dos Abrolhos. / Population is the fundamental unit of conservation and its simplest monitoring tool involves regular sampling over time for population assessing status. One of the Southern Hemisphere humpback whale populations winters at the Brazilian coast typically from May to December where breeding and calving occur. This population, labeled as “breeding stock A” by International Whaling Commission, has shown signs of recovery after the long period of whaling. The goal of this study was to estimate the population size of humpback whales up to 2011, and predict group distribution along the Brazilian coast. Distance sampling methods were implemented and hierarchical Bayesian models were proposed to estimate abundance. Conditional auto-regressive models were used to predict the density in a lattice of 0.5° of latitude and longitude. Population size was estimated at 10,160 whales (Cr.I.95%=6,607-17,692). Highest densities were predicted to occur between Abrolhos Bank and Todos os Santos Bay (BA). The results suggest that the population increase leads to a population expansion beyond Abrolhos Bank.

En épidémiologie des rayonnements ionisants, les erreurs de mesure d’exposition et l’incertitude sur le calcul de la dose absorbée à l’organe constituent des sources d’incertitude importantes entrant en jeu dans la modélisation et l’estimation des relations dose-réponse d’intérêt. Celles-ci peuvent être de nature très complexes dans le cadre d’études de cohortes professionnelles et sont ainsi rarement prises en compte dans ce domaine. Pourtant, lorsque les erreurs de mesure d’exposition ne sont pas ou mal prises en compte, elles peuvent mener à des estimateurs de risque biaisés, à une perte de puissance statistique ainsi qu’à une déformation de ces relations dose-réponse. L’objectif de ce travail est de promouvoir l’utilisation de l’approche hiérarchique bayésienne pour la prise en compte explicite et simultanée des erreurs de mesure d’exposition et des incertitudes de dose intervenant dans les estimations de risques sanitaires radio-induits dans les études de cohortes professionnelles. Plus spécifiquement, des modèles hiérarchiques ont été proposés et inférés afin d’affiner l’estimation actuelle du risque de décès par cancer du poumon associé à une exposition chronique et à faibles doses au radon et ses descendants à vie courte à partir de données issues de la cohorte française des mineurs d’uranium. Ces modèles, connus pour leur souplesse et leur pertinence pour la prise en compte de sources d’incertitude multiples et complexes, sont basés sur une combinaison de sous-modèles probabilistes conditionnellement indépendants. Afin de quantifier l’impact de l’existence d’erreurs de mesure d’exposition partagées et non-partagées sur l’estimation du risque et sur la forme de la relation exposition-risque dans les études de cohortes professionnelles, une étude par simulations a été conduite dans laquelle différentes structures complexes mais réalistes d’erreurs de mesure (pouvant par ailleurs varier dans le temps) ont été considérées. Une élicitation de lois a priori reflétant l’incertitude relative au débit respiratoire - un paramètre important intervenant dans le calcul de la dose absorbée au poumon – a été conduite auprès de trois experts des conditions d’exposition dans les mines d’uranium française et des méthodes de combinaison de dires d’experts ont été mises en œuvre et comparées. Enfin, des algorithmes Monte-Carlo par Chaînes de Markov ont été implémentés sous Python pour mener l’inférence bayésiennes des différents modèles hiérarchiques proposés et ainsi, obtenir des estimations corrigées du risque de décès par cancer du poumon radio-induit dans la cohorte française des mineurs d’uranium. / In radiation epidemiology, exposure measurement error and uncertain input parameters in the calculation of absorbed organ doses are among the most important sources of uncertainty in the modelling of the health effects of ionising radiation. As the structures of exposure and dose uncertainty arising in occupational cohort studies may be complex, these uncertainty components are only rarely accounted for in this domain. However, when exposure measurement is not or only poorly accounted for, it may lead to biased risk estimates, a loss in statistical power and a distortion of the exposure-response relationship. The aim of this work was to promote the use of the Bayesian hierarchical approach to account for exposure and dose uncertainty in the estimation of the health effects associated with exposure to ionising radiation in occupational cohorts. More precisely, we proposed several hierarchical models and conducted Bayesian inference for these models in order to obtain corrected risk estimates on the association between exposure to radon and its decay products and lung cancer mortality in the French cohort of uranium miners. The hierarchical appraoch, which is based on the combination of sub-models that are linked via conditional independence assumptions, provides a flexible and coherent framework for the modelling of complex phenomena which may be prone to multiple sources of uncertainty. In order to compare the effects of shared and unshared exposure uncertainty on risk estimation and on the exposure-response relationship we conducted a simulation study in which we supposed complex and potentially time-varying error structures that are likely to arise in an occupational cohort study. We elicited informative prior distributions for average breathing rate, which is an important input parameter in the calculation of absorbed lung dose, based on the knowledge of three experts on the conditions in French uranium mines. In this context, we implemented and compared three approaches for the combination of expert opinion. Finally, Bayesian inference for the different hierarchical models was conducted via a Markov chain Monte Carlo algorithm implemented in Python to obtain corrected risk estimates on the lung cancer mortality in the French cohort of uranium miners associated with exposure to radon and its progeny.