Dissertations / Theses on the topic 'Multilevel Regression Analysis'

Le Sentiment d'Efficacité Personnelle (SEP) des enseignants fait référence aux croyances que se font ces derniers de leur capacité à accomplir avec succès les tâches liées à leur mission d'enseignement. Le premier objectif de notre recherche vise à répondre aux critiques qui déplorent le manque de validation rigoureuse dont les échelles de SEP ont généralement fait l'objet. Pour ce faire, nous testons, sur base d’analyses factorielles confirmatoires, la validité de trois échelles couramment utilisées dans la littérature anglo-saxonne. La première échelle de mesure, intitulée "Teacher Efficacy Scale" (Gibson & Dembo, 1986) se compose de deux dimensions: le sentiment d’efficacité personnelle mesurant la croyance qu'un enseignant se fait de sa capacité à influencer les apprentissages des élèves, et le sentiment d’efficacité générale mesurant la croyance selon laquelle le corps enseignant est capable d'apporter des changements chez les élèves, en dépit des contraintes extérieures au milieu scolaire. La deuxième échelle intitulée "Teacher Sense of Efficacy Scale" (Tschannen-Moran & Woolfolk Hoy, 2001), mesure le SEP des enseignants selon trois dimensions: l’engagement des élèves, les stratégies d’enseignements et la gestion de la classe. Cette échelle se veut plus spécifique et davantage liée aux différentes tâches pédagogiques auxquelles sont confrontés les enseignants. Enfin, comme le SEP des enseignants n’est pas forcément uniforme à travers les différentes matières enseignées, la troisième échelle de mesure se focalise sur la perception de leur capacité à enseigner les mathématiques. Cette échelle, inspirée de la mesure de McGee et al. (2014) intitulée "Self-Efficacy for Teaching Mathematics Instrument", a été adaptée pour mieux refléter les compétences en mathématiques enseignées dans l’enseignement secondaire de la FW-B. L’échelle distingue trois groupes de compétences: les nombres, les grandeurs et le traitement de données.Une fois ces trois échelles validées, le second objectif de la thèse est d’évaluer dans quelle mesure le SEP des enseignants influence la réussite en mathématiques des élèves de 2e secondaire au CE1D. Nous examinerons l’impact potentiel des différentes dimensions du SEP et émettons l’hypothèse que le SEP des enseignants influence positivement les performances des élèves, mais que l’ampleur de la relation varie selon la dimension étudiée. Cette hypothèse est testée sur base d’une analyse statistique multiniveaux. L’intérêt de cette méthode est qu’elle permet de modéliser l’influence du SEP des enseignants tout en tenant compte des caractéristiques propres aux élèves et aux classes.Nos données sont issues d’une vaste enquête que nous avons organisée au cours de l’année scolaire 2014-2015 au sein des écoles secondaires de la FW-B. Un échantillon représentatif de 164 écoles secondaires a été sélectionné de manière aléatoire. Au sein de ces écoles, tous les élèves de 2e secondaire et leurs enseignants de mathématiques ont été invités à répondre à un questionnaire. Le questionnaire adressé aux élèves était constitué de questions sociodémographiques et d’une épreuve de mathématiques destinée à mesurer les acquis des élèves en début d’année scolaire. Le questionnaire enseignant nous a permis quant à lui de recueillir un ensemble d’information sur leur SEP, leurs attitudes et leurs pratiques pédagogiques. Enfin, grâce à une convention conclue avec l’Administration Générale de l'Enseignement et de la Recherche Scientifique de la FW-B, nous avons eu l’opportunité de coupler nos données aux résultats obtenus, par les élèves de notre échantillon, au CE1D. Notre échantillon final se constitue de 10395 élèves, 598 classes, 388 enseignants et 103 écoles secondaires. Les résultats de nos analyses factorielles confirmatoires remettent en question la validité de la "Teacher Efficacy Scale" développée par Gibson et Dembo en 1986. Ce manque de validité peut s'expliquer par le fait que, contrairement aux deux autres échelles, cette dernière ne reflète pas de manière assez précise la diversité et la complexité du métier d'enseignant. Elle ne permet donc pas de mesurer la concept de sentiment d'efficacité personnelle des enseignants tel que conceptualisé dans la théorie sociocognitive de Bandura (1997). Ces résultats confirment l'idée selon laquelle le sentiment d'efficacité personnelle des enseignants est un concept multidimensionnel qui ne peut pas se mesurer de manière globale. La mesure du sentiment d'efficacité personnelle des enseignants doit être spécifiquement associée à une tâche pédagogique ou à une matière d'enseignement. Cette conclusion va dans le sens des recommandations Bandura qui précise que les croyances d'efficacité doivent être mesurées en relation avec un domaine d’activités précis. Enfin, les résultats de nos analyses multiniveau ne confirment pas la relation direct entre le sentiment d'efficacité personnelle des enseignants et la réussite scolaire des élèves. Aucune des trois dimensions étudiées ne sont significativement liées aux résultats en mathématiques des élèves de 2e secondaire.<br>Doctorat en Sciences politiques et sociales<br>info:eu-repo/semantics/nonPublished

Thesis (PH. D.)--Michigan State University. Measurement and Quantitative Methods, 2008.<br>Title from PDF t.p. (viewed on Sept. 8, 2009) Includes bibliographical references (p. 85-89). Also issued in print.

DNA microarray has become a powerful tool in genetics, molecular biology, and biomedical research. DNA microarray can be used for measuring the genotypes, structural changes, and gene expressions of human genomes. Detection and characterization of multilevel, high-throughput microarray genomic data pose new challenges to statistical pattern recognition and machine learning research. In this dissertation, we propose novel computational methods for analyzing DNA copy number changes and learning the trees of phenotypes using DNA microarray data. DNA copy number change is an important form of structural variations in human genomes. The copy number signals measured by high-density DNA microarrays usually have low signal-to-noise ratios and complex patterns due to inhomogeneous composition of tissue samples. We propose a robust detection method for extracting copy number changes in a single signal profile and consensus copy number changes in the signal profiles of a population. We adapt a solution-path algorithm to efficiently solve the optimization problems associated with the proposed method. We tested the proposed method on both simulation and real CGH and SNP microarray datasets, and observed competitively improved performance as compared to several widely-adopted copy number change detection methods. We also propose a chromosome instability measure to summarize the extracted copy number changes for assessing chromosomal instabilities of tumor genomes. The proposed measure demonstrates distinct patterns between different subtypes of ovarian serous carcinomas and normal samples. Among active research on complex human diseases using genomic data, little effort and progress have been made in discovering the relational structural information embedded in the molecular data. We propose two stability analysis based methods to learn stable and highly resolved trees of phenotypes using microarray gene expression data of heterogeneous diseases. In the first method, we use a hierarchical, divisive visualization approach to explore the tree of phenotypes and a leave-one-out cross validation to select stable tree structures. In the second method, we propose a node bandwidth constraint to construct stable trees that can balance the descriptive power and reproducibility of tree structures. Using a top-down merging procedure, we modify the binary tree structures learned by hierarchical group clustering methods to achieve a given node bandwidth. We use a bootstrap based stability analysis to select stable tree structures under different node bandwidth constraints. The experimental results on two microarray gene expression datasets of human diseases show that the proposed methods can discover stable trees of phenotypes that reveal the relationships between multiple diseases with biological plausibility.<br>Ph. D.

Human Papillomavirus (HPV) is a sexually transmitted infection that causes cervical cancer. A nested three-level logistic regression model was introduced in order to investigate whether, in the IARC HPV prevalence surveys, co-infection with different HPV types occurs more or less frequently than expected if the infections are independent from one another. Two random effects, at individual and study-area level, were specified, while the fixed-effect covariates at individual level were age and lifetime number of sexual partners. The Best Linear Unbiased Predictors (BLUP) technique was used to estimate the random components. The predictions of the random effects at individual level are particularly important because they can be considered as a synthetic estimate of all those residual sources of individual variability, i.e., unmeasured risk factors due to sexual habits, that otherwise could not be accounted for. Individual probabilities of being positive for each HPV type are thus estimated, and the expected vs observed number of infections are compared, given the positivity for a different HPV type. Few positive associations (HPV58 with 33 being the strongest) were found in this analyses. However, the majority of HPV types, particularly the two most oncogenic types, HPV16 and 18, that are also included in the prophylactic vaccine, were not associated with one another.

A partire dagli anni ’80, la diffusione dei metodi statistici, abbinata ai progressi nelle capacità computazionali dei personal computers, ha progressivamente facilitato i ricercatori nel testare empiricamente le proprie teorie. Gli economisti sono diventati in grado di eseguire milioni di regressioni prima di pranzo senza abbandonare le proprie scrivanie. Purtroppo, ciò ha portato ad un accumulo di evidenze spesso eterogenee, quando non contradditorie se non esplicitamente in conflitto. Per affrontare il problema, questa tesi fornirà una panoramica dei metodi meta-analitici disponibili in economia. Nella prima parte verranno introdotte le intuizioni alla base dei modelli gerarchici a fattori fissi e casuali capaci di risolvere le problematicità derivanti dalla presenza di osservazioni non indipendenti. Verrà inoltre affrontato il tema dell’errore sistematico di pubblicazione in presenza di elevata eterogeneità tra gli studi. La metodologia verrà successivamente applicata, nella seconda e terza parte, a due diverse aree della letteratura economica: l’impatto del rapporto banca-impresa sulle prestazioni aziendali e il dibattito sulla relazione fra democrazia e crescita. Mentre nel primo caso la correlazione negativa non è influenzata da fattori specifici ai singoli paesi, il contrario è vero per spiegare l’impatto (statisticamente non significativo) delle istituzioni democratiche sullo sviluppo economico. Quali siano questi fattori è però meno chiaro; gli studiosi non hanno ancora individuato le co-variate – o la corretta misurazione di esse – capaci di spiegare questa discussa relazione.<br>Starting in the late 1980s, improved computing performances and spread knowledge of statistical methods allowed researchers to put their theories to test. Formerly constrained economists became able [to] run millions of regressions before lunch without leaving their desks. Unfortunately, this led to an accumulation of often conflicting evidences. To address such issue, this thesis will provide an overview of the meta-analysis methods available in economics. The first paper will explain the intuitions behind fixed and random effects models in such a framework. It will then detail how multilevel modelling can help overcome hierarchical dependence issues. Finally, it will address the problem of publication bias in presence of high between-studies heterogeneity. Such methods will be then applied, in the second and third papers, to two different areas of the economics literature: the effect of relationship banking on firm performances and the democracy and growth conundrum. Results are far-reaching. While in the first case the documented negative relation is not driven by country-specific characteristics the opposite is true for the (statistically insignificant) impact of democratic institutions on economic growth. What these characteristics are is, however, less clear. Scholars have not yet found the covariates - or their suitable proxies - that matter to explain such much-debated relationship.

A partire dagli anni ’80, la diffusione dei metodi statistici, abbinata ai progressi nelle capacità computazionali dei personal computers, ha progressivamente facilitato i ricercatori nel testare empiricamente le proprie teorie. Gli economisti sono diventati in grado di eseguire milioni di regressioni prima di pranzo senza abbandonare le proprie scrivanie. Purtroppo, ciò ha portato ad un accumulo di evidenze spesso eterogenee, quando non contradditorie se non esplicitamente in conflitto. Per affrontare il problema, questa tesi fornirà una panoramica dei metodi meta-analitici disponibili in economia. Nella prima parte verranno introdotte le intuizioni alla base dei modelli gerarchici a fattori fissi e casuali capaci di risolvere le problematicità derivanti dalla presenza di osservazioni non indipendenti. Verrà inoltre affrontato il tema dell’errore sistematico di pubblicazione in presenza di elevata eterogeneità tra gli studi. La metodologia verrà successivamente applicata, nella seconda e terza parte, a due diverse aree della letteratura economica: l’impatto del rapporto banca-impresa sulle prestazioni aziendali e il dibattito sulla relazione fra democrazia e crescita. Mentre nel primo caso la correlazione negativa non è influenzata da fattori specifici ai singoli paesi, il contrario è vero per spiegare l’impatto (statisticamente non significativo) delle istituzioni democratiche sullo sviluppo economico. Quali siano questi fattori è però meno chiaro; gli studiosi non hanno ancora individuato le co-variate – o la corretta misurazione di esse – capaci di spiegare questa discussa relazione.<br>Starting in the late 1980s, improved computing performances and spread knowledge of statistical methods allowed researchers to put their theories to test. Formerly constrained economists became able [to] run millions of regressions before lunch without leaving their desks. Unfortunately, this led to an accumulation of often conflicting evidences. To address such issue, this thesis will provide an overview of the meta-analysis methods available in economics. The first paper will explain the intuitions behind fixed and random effects models in such a framework. It will then detail how multilevel modelling can help overcome hierarchical dependence issues. Finally, it will address the problem of publication bias in presence of high between-studies heterogeneity. Such methods will be then applied, in the second and third papers, to two different areas of the economics literature: the effect of relationship banking on firm performances and the democracy and growth conundrum. Results are far-reaching. While in the first case the documented negative relation is not driven by country-specific characteristics the opposite is true for the (statistically insignificant) impact of democratic institutions on economic growth. What these characteristics are is, however, less clear. Scholars have not yet found the covariates - or their suitable proxies - that matter to explain such much-debated relationship.

This thesis aims at analysing the attitudes of youngsters in Brussels towards sociological minorities. The term “minorities” is used to refer to the main social groups that suffer from subordination and misrecognition by the wider society according to the philosophical theory of recognition: women, lesbians and gay men, and ethnic minorities. Our dataset is composed of a sample of seventy schools in the Brussels Capital Region. In total, three thousand one hundred and twenty one pupils attending in 2007 the last grade of secondary education participated in the study. About half of the sample consists of pupils with a migrant background originating from about 100 different countries. This cultural diversity, reflecting one of the main characteristics of the population of the Brussels Capital Region, is at the centre of the thesis. <p>Because of the hierarchical structure of the sample (pupils aggregated within schools), the culturally diverse population of our sample and the multidimensionality of prejudice, multilevel multivariate linear responses models were performed. In brief, these models allowed us to interpret items regrouped according to their common variation across social (and ethnic) groups and not according to their a priori content similarities. Furthermore, these models allowed us to integrate three different research traditions on prejudice: social psychology on the dimensionality of prejudice, sociology on the impact of socio demographic characteristics on prejudice and school effectiveness research on the role schools may play in reducing pupils’ prejudice. With these models, we could demonstrate the capacity of multilevel techniques to encompass the complexity of prejudice and norms, and to provide an interdisciplinary approach of social processes. <p>Besides the impact of gender and socio economic differences on prejudice, the association between ethnic origin and prejudice was the focus of the analysis at the individual level. Hence, the empirical literature showed that respondents of foreign descent and respondents from the receiving society do not hold similar attitudes towards minorities. This association was investigated in a twofold strategy: after having assessed ethnic differences on the different kinds of prejudice, the explanatory power of possible mediators -such as the experience of group-level institutional discrimination or the bidimensional identification- on this association was tested. The choice of these mediators was influenced by different disciplines of the social sciences. Hence, besides the empirical literature specific to the topic of prejudice, these mediators are derived from theories of political sciences, of sociology of immigration, of social psychology and of cross-cultural psychology. The results showed that these mediators could indeed explain to a large extent ethnic differences on prejudice towards minorities. <p>On the school level, we have shown that the impact schools may have on pupils’ prejudice is a differentiated one. Hence, this impact varies according to both the targets and the dimensions of prejudice. Moreover, besides school institutional characteristics, several contextual characteristics were investigated such as the cultural and social diversity within a school. Our results showed that the impact on prejudice of social and cultural diversity within schools was non-significant. This is, however, most probably related to a masking effect by the specificities of the education landscape in Brussels: differences between schools are huge and homogeneity within schools is important, given that the educational field is highly segregated both in social and in cultural terms. The implications of these results based on an interdisciplinary approach for future research and for policymakers are discussed. <p><br>Doctorat en Sciences politiques et sociales<br>info:eu-repo/semantics/nonPublished

Increasing urbanization across the world has led to increased research on ecology in urban settings in the last decade. Urban ecological studies have investigated both impacts of urban development on native ecosystems and the dynamics of urban environments themselves as ecosystems. In both areas of research, streams of urban areas have an important part to play because their position in the landscape makes these ecosystems particularly vulnerable to impacts associated with landcover change. Urban stream ecosystems are affected by multiple stressors and their effects are synthetized in the “urban stream syndrome” theorized in Walsh et al. 2005. Consistent symptoms of the urban stream include flashier hydrograph, elevated concentrations of nutrients and contaminants, altered channel morphology and stability and reduced biodiversity, with increased tolerant species. These ecological effects are often accompanied by other symptoms not observed in all urban areas, such as reduced baseflow and increased suspended solids. In impaired freshwater ecosystems, it is known that ecological integrity can be subdivided into two components, structural and functional integrity. Structural indicators of ecosystem health may be defined as the qualitative and quantitative composition of biological communities. Fish and macroinvertebrate assemblages have been the main focus for assessing structural integrity, although a variety of alternative targets such as benthic algal communities, protozoans, and macrophytes have also been used. Macroinvertebrate assemblages play a central ecological role in many stream ecosystems and are among the most ubiquitous and diverse organisms in fresh waters. Macroinvertebrates are easily recognizable and classifiable and some taxa are representative of every different habitat and condition (sensibility or tollerance to pollution and environmental changes) and so it is easy to aggregate results of macrobenthos analyses into synthetic indeces (such as STAR_ICMi). Function indicators instead, that have a much shorter history, are complementary to structural indicators and refer to the autoecology of biological communities and ecological attributes within the ecosystem in which they are located. In Water Framework Directive, develops by European Union to advance more comprehensive water legislation, the river basins with above mentioned characteristics are defined heavily modified water bodies (HMWBs). HMWBs have unique water quality characteristics that, in most cases, are comparatively different from normal stream conditions upstream of the discharge or at regional reference sites. Reference sites are commonly used in bioassessment studies to identify undisturbed or pristine conditions and hence management targets. The increase of urban development often results in the absence of reference sites in HMWBs and this leads in difficulties to define a target condition for restoring urban stream sites. The WFD requires that all waters achieve good ecological status and only slightly deviate from natural reference conditions, which has become the main objective of most restoration projects in Europe. The ecological status is quantified in many European member states using multi-metric indices, and good ecological status corresponds to a specific score value. However, there is little information on the limiting effects of large-scale pressures on the biological metrics. As suggested by numerous research works, the scale to approach river investigations can be considered from the microhabitat level to basin scale. A river may be analysed across a variety of levels, which can be ordered into a hierarchy, with different degree of sensitivity and recovery time. Impacts of human activity are becoming increasingly unacceptable to a global community that focuses on environmental sustainability. Therefore, whole catchment approach management have been developed to preserve stream ecosystems or restore damaged ecosystems, and mitigate against further damage. The individuation of which factors set limits to biological community development and their respective values is of great interest for river managers and river restoration campaigns. In urban streams is usually hard to assess causal relationships among specific stressors and responses of biological communities using the most common statistical tools. Using macroinvertebrate assemblages as biological indicators in micro- and mesohabitat level works, applied statistics may be viewed as an elaboration of the linear regression model and associated estimation methods of least square. In whole basin analyses, data variability is high and classic statistical approach may even become uninformative. Moreover, the effects of many stressors (local and global) may influence simultaneously the response of biological community leading to a decrease of statistical model fit. In this perspective, alternative statistical approaches are necessary. In 1978 Koenker and Bassett theorized the quantile regression in econometric sciences, a robust alternatives to the least squares estimator for the linear model. Other authors introduced this kind of regression in ecology declaring that quantile regression allows the various stressors to be considered as “constraints” to the distribution of biological communities, without compromising the model causal relationship. Aim of this work is to assess the overall pressure of human activities in river basins of Lombardy piedmont and floodplain area and to relate changes in the biological communities as a result of habitat loss and changes in both hydromorphological and physico-chemical properties. In this area, many rivers have a “channelized” nature with straight section, clear of river bank tree and uniform bed morphology. Flow regulation and modification have also been widespread. The quantity and timing of water availability have been altered for irrigation and industrial purposes, through the construction of dams and reservoir for water supply. Changes in water quality are also common, in particular in lowland areas where urbanization and agriculture are more strong. For these reasons, the work is focusing on different scale (microhabitat, site, river reach and basin levels) to have a better resolution and understanding of existing dynamics among structural and functional indicators and pressures in impaired environments. These areas undergo different stresses (habitat loss, changes in physico-chemical properties and changes in flow) that affect the integrity of the ecosystems. Assessing the condition of ecosystems is a prerequisite to reduce the induced anthropogenic pressure. Decision-making in river restoration programs can also be helped by multilevel kind of information.

Students transitioning into college from public school require more than just academic readiness; they also need the personal attributes that allow them to successfully transition into a new community (Braxton, Doyle, Hartley III, Hirschy, Jones, & McLendon, 2014; Nora, 2002; Nora, 2004; Tinto, 1975). Rural students have a different educational experience than their peers at schools in suburban and urban locations (DeYoung & Howley, 1990; Gjelten, 1982). Additionally, the resources, culture, and educational opportunities at rural schools also vary among different types of rural communities. Although some studies have examined the influence of rural students' academic achievement on college access and success, little research has analyzed the relationship between students of different types of rural communities and their persistence in post-secondary education. This study examined the likelihood for college-going students from three different types of rural communities to successfully transition into and persist at a four-year residential college. Multilevel logistic modeling was used to analyze the likelihood for students to persist in college for up to two academic years based on whether they were from rural tourist communities, college communities, and other rural communities. The analysis controlled for a variety of student and high school factors. Findings revealed that student factors related to poverty and academic readiness have the greatest effects, while the type of rural community has no significant influence on college persistence.

In the last three decades recursive residuals and estimation have received extensive attention as important and powerful tools in providing a diagnostic test of the structural change and functional misspecification in regression models. Recursive residuals and their relationship with recursive estimation of regression parameters have been developed for fixed effect models. Such residuals and estimation have been used to test the constancy of regression models over time and their usage has been suggested for almost all areas of regression model validation. These recursive techniques have not been developed for some of the more recent generalisations of Linear Models such as Linear Mixed Models (LMM) and their important extension to Generalised Linear Mixed Models (GLMM) which provide a suitable framework to analyse a variety of special problems in an unified way. The aim of this thesis is to extend the idea of recursive residuals and estimation to Mixed Models particularly for LMM and GLMM. Recurrence formulae are developed and recursive residuals are defined.

Housing deprivation is an important dimension of poverty. It is thus a key challenge of policy makers to secure decent housing. The purpose of this paper is to analyze the link between housing tenure types and housing deprivation in 24 European countries. Empirical analyses are based on EU-SILC 2007, enabling comparisons of deprivation across a large set of countries. A multilevel framework is employed. Two competing hypothesis are evaluated. First, whether a rental sector targeted towards low-income households, known as social housing, is successful in achieving adequate housing standards. Second, if a unified rental system covering broader income groups lowers the risk of housing deprivation. Housing deprivation is measured in terms of experiencing overcrowding and while also exhibiting any of the following deficits: a leaking roof; no bath/shower; no indoor toilet; or a dwelling considered too dark. Findings indicate a negative association between the size of the rental sector and the prevalence of housing deprivation. The organization of the rental sector appears most crucial and only the strategy of a rental sector encompassing broader parts of the population significantly reduces the prevalence of housing deprivation and its latent components. The association is robust in terms of confounding factors at the individual level and central country level contextual variables.

BACKGROUND:Interruption of vector-borne transmission of Trypanosoma cruzi remains an unrealized objective in many Latin American countries. The task of vector control is complicated by the emergence of vector insects in urban areas.METHODS:Utilizing data from a large-scale vector control program in Arequipa, Peru, we explored the spatial patterns of infestation by Triatoma infestans in an urban and peri-urban landscape. Multilevel logistic regression was utilized to assess the associations between household infestation and household- and locality-level socio-environmental measures.RESULTS:Of 37,229 households inspected for infestation, 6,982 (18.8%<br>95% CI: 18.4 - 19.2%) were infested by T. infestans. Eighty clusters of infestation were identified, ranging in area from 0.1 to 68.7 hectares and containing as few as one and as many as 1,139 infested households. Spatial dependence between infested households was significant at distances up to 2,000 meters. Household T. infestans infestation was associated with household- and locality-level factors, including housing density, elevation, land surface temperature, and locality type.CONCLUSIONS:High levels of T. infestans infestation, characterized by spatial heterogeneity, were found across extensive urban and peri-urban areas prior to vector control. Several environmental and social factors, which may directly or indirectly influence the biology and behavior of T. infestans, were associated with infestation. Spatial clustering of infestation in the urban context may both challenge and inform surveillance and control of vector reemergence after insecticide intervention.

This longitudinal study investigates firm-survival in a peripheral region. The analysis relies on a unique longitudinal dataset, encompassing all firms in 17 Stockholm Archipelago islands during 2000-2019, collected through data triangulation methods. The study employs multivariate analysis accomplished by three-level logistic regression models of repeated observations (level-1) of the same distinct firms (level-2) situated in specific islands (level-3). The main novel results suggest that firms on islands with higher population density have an increased probability of exit – specifically, that there exists an overcrowding of local markets and a harsher selection process in these islands. While time-distance to the mainland have been discussed as problematic, the effect on firm-survival is insignificant. However, local access to essential services and infrastructures significantly lowers the likelihood of firm-exit. Islands with increasing institutional thickness have increased community dynamics with more knowledge spillovers, community-level learning, and entrepreneurial ecosystems, leading to a higher likelihood of firm-survival. A higher ratio of summer visitors increases the probability of exit, suggesting that firms on islands with seasonal dependability may have difficulties surviving the off-season.<br>Trots dess närhet till Sveriges största och snabbast växande marknad delar Stockholms skärgård många drag med andra regioner som befinner sig i periferin, det vill säga utkanten. Bland annat har skärgården svårigheter att dra nytta av den ekonomiska dynamik som är karakteristisk för centrala regioner. Trots den problematik som kan vara typisk för perifera områden (såsom brist på resurser och avfolkning), betonar forskare att beslutsfattare måste utgå ifrån den lokalspecifika och regionala kontexten. Små och medelstora företag i periferin förväntas inte enbart bidra med ökade intäkter till regionen, utan förväntas även tillmötesgå sysselsättningsefterfrågan. Frågan om vilka företag som överlever, och inte minst förklaringarna till företags överlevad, är därför särskilt viktig i dessa regioner. Trots att orsakerna till företags överlevnad länge diskuterats inom forskningen, råder det brist på studier som tar upp den kontext som avser periferi och faktorer som är betydelsefulla för en specifik kontext. Denna studie utgör ett bidrag till en sådan analys. Studiens resultat visar att överlevnadsmöjligheterna är sämre för företag som befinner sig på öar med högre andel fastboendebefolkning. Detta indikerar att på större öar, med en relativt sett högre befolkningsnivå, är konkurrensen mer påtaglig. Vidare, trots att transportmöjligheter till fastlandet ofta anges som problem i diskussioner, slår studien fast att tidsavståndet till huvudorter på fastlandet inte är viktigt för företags överlevnadsmöjligheter. Däremot har företag sämre utsikter för överlevnad på öar med högre andel sommargäster i relation till vinterbesökare. Tillgången till fiber/bredband, livsmedelsbutiker som är öppna året runt, och förskolor bidrar betydligt till överlevnadsmöjligheterna. Vidare konstaterar studien att ett mer aktivt föreningsliv på en ö ökar möjligheterna för överlevnad. För att komma fram till dessa samt andra resultat, har studien använt sig av en longitudinell ansats, som innebär att studieobjekten (företagen) följs över tid, liksom ett unikt empiriskt underlag. Detta material har samlats från flera olika typer källor, underlag och databaser som beskriver både öar och företag i Stockholms skärgård, där undersökningsperioden är mellan år 2000 och år 2019. Vidare tillämpar studien en i forskning om företags överlevnad tidigare mindre beprövad statistisk metod: i korthet undersöker studien företag och öarna där de finns, som om dessa vore enskilda ”individer”. Dessa ”individer” följs från sin födsel –från att de bildas – till dess att de dör, det vill säga läggs ned. Under tiden ”individerna” följs, så undersöks även vilken betydelse de yttre betingelserna på öarna liksom faktorer i företagens omgivning har för deras överlevnadsförmåga. Specifikt studeras 1 341 företag på 17 av Stockholms skärgårdens öar (kärnöar).

Thesis advisor: Henry Braun<br>This study evaluates the accuracy, precision, and stability of three different methods of cross-survey analysis in order to determine their suitability for estimating the proportions of low-incidence populations. Population parameters of size and demographic distribution are necessary for planning and policy development. The estimation of these parameters for low-incidence populations poses a number of methodological challenges. Cross-survey analysis methodologies offer an alternative to generate useful, low-incidence population estimates not readily available in today's census without conducting targeted, costly surveys to estimate group size directly. The cross-survey methods evaluated in the study are meta-analysis of complex surveys (MACS), pooled design-based cross-survey (PDCS), and Bayesian multilevel regression with post-stratification (BMRP). The accuracy and precision of these methods were assessed by comparing the estimates of the proportion of the adult Jewish population in Canada generated by each method with benchmark estimates. The stability of the estimates, in turn, was determined by cross-validating estimates obtained with data from two random stratified subsamples drawn from a large pool of US surveys. The findings of the study indicate that, under the right conditions, cross-survey methods have the potential to produce very accurate and precise estimates of low-incidence populations. The study did find that the level of accuracy and precision of these estimates varied depending on the cross-survey method used and on the conditions under which the estimates were produced. The estimates obtained with PDCS and BMRP methodologies were more accurate than the ones generated by the MACS approach. The BMRP approach generated the most accurate estimates. The pooled design-based cross-survey method generated relatively accurate estimates across all the scenarios included in the study. The precision of the estimates was found to be related to the number of surveys considered in the analyses. Overall, the findings clearly show that cross-survey analysis methods provide a useful alternative for estimation of low-incidence populations. More research is needed to fully understand the factors that affect the accuracy and precision of estimates generated by these cross-survey methods<br>Thesis (PhD) — Boston College, 2016<br>Submitted to: Boston College. Lynch School of Education<br>Discipline: Educational Research, Measurement and Evaluation

Les objectifs des entreprises n’ont pas cessé d’évoluer. Traditionnellement, la maximisation du profit a été considérée comme l’objectif ultime de l’activité de toute entreprise. Aujourd’hui, les managers déclinent plusieurs autres objectifs comme le profit à long terme plutôt qu'à court terme, l’image de marque, ou encore le respect de l’environnement (Boiral, 2006). Ainsi, pour identifier les motivations d’engagement des entreprises dans la responsabilité sociale (RSE) nous avons mobilisé, l’ensemble de la revue de littérature sur le sujet, en se basant sur le cadre d’analyse multi-niveaux identifié par Wood (1991). Cette étude nous a permis de mettre en place un modèle de recherche sur trois niveaux qui explique les motivations d’engagement des entreprises dans la RSE. Ce modèle de recherche a été testé sur 94 entreprises qui œuvrent dans le secteur industriel Algérien. Les résultats ont confirmé en partie nos hypothèses. Par conséquent, l’engagement volontaire des entreprises dans la RSE s’explique par : les valeurs idéalistes du chef d’entreprise, la réduction des coûts de production, l’anticipation sur la législation, l’avantage concurrentiel, la subvention de l’état et à la taille de l’entreprise<br>The objectives of the compagnies have not stopped evolving. Traditionally profit maximization was considered as the ultimate goal of any business activity. Today, managers declined several alternative objectives such as long term profit rather than short one, brand, or respect for the environment, Boiral (2006). Thus, to identify the corporate commitments motivations into the social responsibility (CSR), we investigated all literature on the subject, based on the analysis of multi- level framework identified by Wood (1991). This study has allowed us to establish a research model on three levels, which explains the motivations of corporate commitments to CSR. This research model has been tested on 94 companies operating in the Algerian industrial sector. The results partly confirmed our hypotheses. Therefore, the compagnies voluntary commitment in CSR is explained by the idealistic values of the entrepreneur, the reduction of production costs, the anticipation of the legislation, competitive advantage, the state subsidy and the company size

Submitted by Maicon Juliano Schmidt (maicons) on 2015-04-28T19:47:26Z No. of bitstreams: 1 Daniel Rodrigues.pdf: 1135227 bytes, checksum: 8dd259ca27667826c215ed0567d0b320 (MD5)<br>Made available in DSpace on 2015-04-28T19:47:26Z (GMT). No. of bitstreams: 1 Daniel Rodrigues.pdf: 1135227 bytes, checksum: 8dd259ca27667826c215ed0567d0b320 (MD5) Previous issue date: 2013-09-25<br>Nenhuma<br>Atualmente, os casos de interrupção na cadeia de suprimentos da carne bovina no Brasil estão relacionados, principalmente, aos eventos de contaminação. Embora a maioria das fontes de contaminação estejam vinculadas ao campo (subsistema produção), é nas indústrias frigoríficas (subsistema industrialização) que estão inseridas as condições teoricamente mais adequadas para o efetivo controle desses eventos. Por esse motivo, em termos de importância na cadeia de suprimentos, o subsistema industrialização pode ser considerado o elo que mais impacta para a sanidade e qualidade do produto final. Esta pesquisa tem como objetivo analisar como as características do sistema de inspeção sanitária estão associadas à detecção dos casos de contaminação na cadeia de suprimentos da carne bovina. A amostra é composta por 103 estabelecimentos frigoríficos, certificados com o selo de inspeção estadual, e por 19 Unidades Regionais de Inspeção (SRA) do Rio Grande do Sul. Para análise estatística, a técnica utilizada foi a análise de regressão de contagem multinível, sendo um dos fatores relevantes para a escolha a preservação dos níveis hierárquicos dos dados. Ao que se refere à SRA, os resultados apontaram a influência de variáveis como o número de Empresas Atendidas, Recursos Internos e o Coeficiente de Variação de Abates nos casos de contaminação detectados. No âmbito da Empresa, os resultados apontaram que o porte, definido a partir do número de Animais Abatidos, apresentou relação com os casos de contaminação verificados. Nos testes de interação entre as variáveis dos diferentes níveis, Animais Abatidos (nível Empresa) apresentou uma interação considerada significativa com a variável de segundo nível Recursos Internos (nível SRA). À luz da Teoria Institucional, confirmou-se o papel do Estado como uma importante força de coerção do ambiente (isomorfismo regulativo) que pressiona as empresas para que se tornem mais homogêneas, principalmente, nas operações de abate e ratifica que as profissões (isomorfismo normativo), através do Médico Veterinário e Auxiliar de Inspeção, também constitui-se em uma importante força do ambiente que induz os estabelecimentos frigoríficos a se assemelharem. Nas Implicações gerenciais os resultados indicam que o Sistema de Inspeção Sanitária possui uma considerável associação com os eventos de Contaminação de Detectados, principalmente, por fatores como a estrutura interna da Unidade Regional, a capacidade e quantidade de atendimentos suportada, e as condições estruturais das empresas atendidas.<br>Nowadays, the cases of interruption at the beef supplying chain in Brazil, are connected, mainly, to the events of contamination. Although the majority of contamination sources are linked to the country area (subsystem production), it is inside the industries (subsystem industrialization) that are inserted the conditions, more appropriated, theoretically, to the effective control in these events. For that reason, related to the importance at the supplying chain, the subsystem industrialization can be considered the linking that causes more impact to the sanity and quality of the final product. This research aimed to analyze how the characteristics of the Sanitary Inspection System are linked to the detection of contamination cases at the beef supply chain. The sample is composed by 103 cold-store buildings, certificated with the state inspection stamp, and by 19 Regional Units of Inspection in Rio Grande do Sul. To statistical analyzes, the used technique was the regression analysis at multilevel counting, being one of the most relevant facts to the choice the preservation of hierarchic levels of data. Related to the Sanitary Inspection System, the results point to the influence of aspects as the number of Considered Companies, Inner Resources and the Coefficient of Variation of Slaughtering at the cases of detected contamination. Related to the Company, the results point to the transport, defined from the number of animals slaughtered, presented relation to the cases of contamination detected. In the tests of interaction between the variables of different levels, Animals Slaughtered (Company level) showed an interaction considered meaningful with a variable of second level of the Inner Resources (Resources level). To the light of Institutional Theory, it was confirmed the rule of the State as an important force of coercion of the environment (regulative isomorphism) that pressures the companies so that they become more homogeneous, mainly, in the operations of slaughtering and it ratifies that the professions (normative isomorphism), through the Veterinarian and Assistant of Inspection, also consists in an important force of the environment that induces the packing plants to be similar. In the management implications, the results indicate that the System of Sanitary Inspection has a considerable association with the Detected events of Contamination, mainly, for factors as the internal structure of the 8 Regional Unit, the capacity and amount of supported requests, and the structural conditions of attended companies.

In the last three decades recursive residuals and estimation have received extensive attention as important and powerful tools in providing a diagnostic test of the structural change and functional misspecification in regression models. Recursive residuals and their relationship with recursive estimation of regression parameters have been developed for fixed effect models. Such residuals and estimation have been used to test the constancy of regression models over time and their usage has been suggested for almost all areas of regression model validation. These recursive techniques have not been developed for some of the more recent generalisations of Linear Models such as Linear Mixed Models (LMM) and their important extension to Generalised Linear Mixed Models (GLMM) which provide a suitable framework to analyse a variety of special problems in an unified way. The aim of this thesis is to extend the idea of recursive residuals and estimation to Mixed Models particularly for LMM and GLMM. Recurrence formulae are developed and recursive residuals are defined.<br>Doctor of Philosophy (PhD)

In this thesis a number of statistical methods have been developed and applied to habitat suitability modelling for rare and threatened species. Data available on these species are typically limited. Therefore, developing these models from these data can be problematic and may produce prediction biases. To address these problems there are three aims of this thesis. The _rst aim is to develop and implement frequentist and Bayesian statistical modelling approaches for these types of data. The second aim is develop and implement expert elicitation methods. The third aim is to apply these novel approaches to Australian rare and threatened species case studies with the intention of habitat suitability modelling. The _rst aim is ful_lled by investigating two innovative approaches for habitat suitability modelling and sensitivity analysis of the second approach to priors. The _rst approach is a new multilevel framework developed to model the species distribution at multiple scales and identify excess zeros (absences outside the species range). Applying a statistical modelling approach to the identi_cation of excess zeros has not previously been conducted. The second approach is an extension and application of Bayesian classi_cation trees to modelling the habitat suitability of a threatened species. This is the _rst `real' application of this approach in ecology. Lastly, sensitivity analysis of the priors in Bayesian classi_cation trees are examined for a real case study. Previously, sensitivity analysis of this approach to priors has not been examined. To address the second aim, expert elicitation methods are developed, extended and compared in this thesis. In particular, one elicitation approach is extended from previous research, there is a comparison of three elicitation methods, and one new elicitation approach is proposed. These approaches are illustrated for habitat suitability modelling of a rare species and the opinions of one or two experts are elicited. The _rst approach utilises a simple questionnaire, in which expert opinion is elicited on whether increasing values of a covariate either increases, decreases or does not substantively impact on a response. This approach is extended to express this information as a mixture of three normally distributed prior distributions, which are then combined with available presence/absence data in a logistic regression. This is one of the _rst elicitation approaches within the habitat suitability modelling literature that is appropriate for experts with limited statistical knowledge and can be used to elicit information from single or multiple experts. Three relatively new approaches to eliciting expert knowledge in a form suitable for Bayesian logistic regression are compared, one of which is the questionnaire approach. Included in this comparison of three elicitation methods are a summary of the advantages and disadvantages of these three methods, the results from elicitations and comparison of the prior and posterior distributions. An expert elicitation approach is developed for classi_cation trees, in which the size and structure of the tree is elicited. There have been numerous elicitation approaches proposed for logistic regression, however no approaches have been suggested for classi_cation trees. The last aim of this thesis is addressed in all chapters, since the statistical approaches proposed and extended in this thesis have been applied to real case studies. Two case studies have been examined in this thesis. The _rst is the rare native Australian thistle (Stemmacantha australis), in which the dataset contains a large number of absences distributed over the majority of Queensland, and a small number of presence sites that are only within South-East Queensland. This case study motivated the multilevel modelling framework. The second case study is the threatened Australian brush-tailed rock-wallaby (Petrogale penicillata). The application and sensitivity analysis of Bayesian classi_cation trees, and all expert elicitation approaches investigated in this thesis are applied to this case study. This work has several implications for conservation and management of rare and threatened species. Novel statistical approaches addressing the _rst aim provide extensions to currently existing methods, or propose a new approach, for identi _cation of current and potential habitat. We demonstrate that better model predictions can be achieved using each method, compared to standard techniques. Elicitation approaches addressing the second aim ensure expert knowledge in various forms can be harnessed for habitat modelling, a particular bene_t for rare and threatened species which typically have limited data. Throughout, innovations in statistical methodology are both motivated and illustrated via habitat modelling for two rare and threatened species: the native thistle Stemmacantha australis and the brush-tailed rock wallaby Petrogale penicillata.

In this thesis a number of statistical methods have been developed and applied to habitat suitability modelling for rare and threatened species. Data available on these species are typically limited. Therefore, developing these models from these data can be problematic and may produce prediction biases. To address these problems there are three aims of this thesis. The _rst aim is to develop and implement frequentist and Bayesian statistical modelling approaches for these types of data. The second aim is develop and implement expert elicitation methods. The third aim is to apply these novel approaches to Australian rare and threatened species case studies with the intention of habitat suitability modelling. The _rst aim is ful_lled by investigating two innovative approaches for habitat suitability modelling and sensitivity analysis of the second approach to priors. The _rst approach is a new multilevel framework developed to model the species distribution at multiple scales and identify excess zeros (absences outside the species range). Applying a statistical modelling approach to the identi_cation of excess zeros has not previously been conducted. The second approach is an extension and application of Bayesian classi_cation trees to modelling the habitat suitability of a threatened species. This is the _rst `real' application of this approach in ecology. Lastly, sensitivity analysis of the priors in Bayesian classi_cation trees are examined for a real case study. Previously, sensitivity analysis of this approach to priors has not been examined. To address the second aim, expert elicitation methods are developed, extended and compared in this thesis. In particular, one elicitation approach is extended from previous research, there is a comparison of three elicitation methods, and one new elicitation approach is proposed. These approaches are illustrated for habitat suitability modelling of a rare species and the opinions of one or two experts are elicited. The _rst approach utilises a simple questionnaire, in which expert opinion is elicited on whether increasing values of a covariate either increases, decreases or does not substantively impact on a response. This approach is extended to express this information as a mixture of three normally distributed prior distributions, which are then combined with available presence/absence data in a logistic regression. This is one of the _rst elicitation approaches within the habitat suitability modelling literature that is appropriate for experts with limited statistical knowledge and can be used to elicit information from single or multiple experts. Three relatively new approaches to eliciting expert knowledge in a form suitable for Bayesian logistic regression are compared, one of which is the questionnaire approach. Included in this comparison of three elicitation methods are a summary of the advantages and disadvantages of these three methods, the results from elicitations and comparison of the prior and posterior distributions. An expert elicitation approach is developed for classi_cation trees, in which the size and structure of the tree is elicited. There have been numerous elicitation approaches proposed for logistic regression, however no approaches have been suggested for classi_cation trees. The last aim of this thesis is addressed in all chapters, since the statistical approaches proposed and extended in this thesis have been applied to real case studies. Two case studies have been examined in this thesis. The _rst is the rare native Australian thistle (Stemmacantha australis), in which the dataset contains a large number of absences distributed over the majority of Queensland, and a small number of presence sites that are only within South-East Queensland. This case study motivated the multilevel modelling framework. The second case study is the threatened Australian brush-tailed rock-wallaby (Petrogale penicillata). The application and sensitivity analysis of Bayesian classi_cation trees, and all expert elicitation approaches investigated in this thesis are applied to this case study. This work has several implications for conservation and management of rare and threatened species. Novel statistical approaches addressing the _rst aim provide extensions to currently existing methods, or propose a new approach, for identi _cation of current and potential habitat. We demonstrate that better model predictions can be achieved using each method, compared to standard techniques. Elicitation approaches addressing the second aim ensure expert knowledge in various forms can be harnessed for habitat modelling, a particular bene_t for rare and threatened species which typically have limited data. Throughout, innovations in statistical methodology are both motivated and illustrated via habitat modelling for two rare and threatened species: the native thistle Stemmacantha australis and the brush-tailed rock wallaby Petrogale penicillata.

Esta tesis doctoral está basada en el estudio de los factores determinantes de la duración de la incapacidad temporal por contingencia común (ITcc). Se examina la variabilidad geográfica de la duración de la ITcc entre comarcas de Cataluña para episodios de ITcc en general y para dos patologías frecuentes, trastornos musculoesqueléticos (TME) y trastornos mentales. Se utilizan datos de cohortes de episodios de ITcc cedidos por el Institut Català d’Avaluacions Mèdiques i Sanitàries (ICAMS) de la Generalitat de Catalunya. Se analizaron todos los primeros episodios de ITcc finalizados en el año 2007 y 2010 estudiando factores individuales (sexo, edad, diagnóstico, entidad gestora del episodio, régimen de afiliación a la Seguridad Social y rama de actividad económica) y/o contextuales relacionados con recursos sanitarios (número de áreas básicas de salud) y socioeconómicos (cuota de mercado y tasa de desempleo) que podrían explicar la variabilidad observada. Se utilizaron modelos de regresión multinivel de riesgos proporcionales con episodios anidados en comarcas. También se propone un modelo de fragilidad condicional basado en un enfoque Poisson para analizar la duración de la ITcc (u otro evento de interés) en presencia de eventos repetidos para un mismo individuo, y se muestra la utilidad del modelo para analizar dicha duración en grandes bases de datos. Se utilizaron episodios de ITcc finalizados en el año 2007 por trastorno mental y por neoplasia, a partir de los cuales se comparó empíricamente el modelo de fragilidad condicional (CFM) y el enfoque propuesto basado en un modelo de fragilidad condicional Poisson (CFPM).<br>This thesis is based on the study of the determinants of the duration of sickness absence (SA). We examined the geographic variability of the SA duration between comarcas of Catalonia for SA in general and for two common groups of disorders, musculoskeletal disorders (MSDs) and mental health disorders. Cohort data of SA episodes ceded by the Institut Català d’Avaluacions Mèdiques i Sanitàries (ICAMS) of the Generalitat of Catalunya were used. All first SA episodes ending in 2007 and 2010 were analyzed studying individual factors (sex, age, diagnosis, entity managing the sick leave, employment status, and economic activity branch) and contextual factors related to health resources (number of basic health areas) and socioeconomic indicators (market share and unemployment rate) that could explain the observed variability. Multilevel proportional hazard regression models with episodes nested in comarcas were used. This thesis also proposes using a conditional frailty model based on a Poisson approach for analyzing SA duration (or other event of interest) in the presence of repeated events in the same individual, and demonstrates the usefulness of such a model to analyze large datasets. SA episodes ending in 2007, caused by mental health disorders and neoplasms were used, from which the conditional frailty model (CFM) and a novel approach based on a conditional frailty Poisson model (CFPM) were compared empirically.

Le cancer du sein est actuellement dans les pays occidentaux le premier cancer chez la femme, en termes d’incidence et de mortalité (taux standardisés de 101,5 et 17.7 pour 100 000 personnes années en 2005 respectivement). De très nombreux facteurs de risque et facteurs pronostiques sont déjà connus et étudiés, plusieurs axes de recherche sont développés sur toutes les étapes de la maladie, mais l’influence des facteurs socio-économiques et géographiques, aux niveaux individuel et environnemental n’avait pas encore été étudiée en France sur le cancer du sein.L’objectif général de ce travail était d’explorer cette influence par différents moyens afin d’en tirer des connaissances et une application pratique dans la prévention du cancer du sein, qu’elle soit primaire, secondaire ou tertiaire.Dans notre première étude nous avons montré que les femmes d’un niveau socio-éducatif faible étaient moins à même d’avoir bénéficié d’au moins une mammographie dans les 6 ans ou d’au moins un suivi gynécologique dans les 3 ans précédant leur diagnostic de cancer du sein. Egalement elles ont un stade de diagnostic plus avancé que les femmes de niveau socio-éducatif plus élevé. Ces variables sont ensuite retrouvées comme facteurs pronostiques péjoratifs de la survie. Dans notre seconde étude nous avons montré que l’accès à un chirurgien spécialisé dans les interventions du cancer du sein, gage d’une meilleure survie, était influencé par le niveau socio-économique du lieu de résidence de la patiente, ainsi que par son éloignement géographique par rapport aux centres de traitement de référence du cancer, où travaillent les chirurgiens spécialisés. Dans notre troisième étude nous avons montré qu’à l’inverse de nombre de cancers, l’incidence du cancer du sein était plus élevée dans les zones socio-économiquement plus favorisées, et ce quelle que soit la classe d’âge de la patiente, phénomène pour lequel nous n’avons pas vraiment d’explication, surtout pour les femmes les plus jeunes. Enfin dans notre quatrième étude actuellement en cours, nous avons pour objectif d’étudier au niveau individuel, conjointement avec le nouvel indice de défavorisation européen adapté à la France, en quoi le degré de richesse économique et sociale et la proximité des services médicaux des patientes atteintes de cancer du sein joue sur le stade de la tumeur, l’accès et les modalités de traitement, et la survie<br>In developed countries, breast cancer is currently the leading cancer in women in terms of incidence and mortality (standardized rate of 101.5 and 17.7 per 100,000 person-years in 2005, respectively). Many risk factors and prognostic factors have been studied and are well known. Research is under way with regard to every step in the development of breast cancer, but the impact of socio-economic and geographic factors, at the individual and environmental level with regard to the disease have never been studied in France.The general aim of this work was to explore the impact of these factors in different ways to build on our knowledge and to develop practical applications in the primary, secondary or tertiary prevention of breast cancer.In our first study, we showed that women with a low socio-educational level were less likely to have benefited from at least one mammography within the 6 years or at least one gynaecological consultation within the 3 years before the diagnosis of breast cancer. These women also had a more advanced tumour at diagnosis than did women with a higher socio-educational level. These variables also came to light as predictors of a poor prognosis in terms of survival. In our second study, we showed that access to a surgeon specialised in breast cancer surgery, which is associated with better survival, was influenced by the socio-economic level of the patient’s place of residence, as well as the distance between the patient’s home and reference centres for cancer treatment, where the specialised surgeons work. In our third study, we showed that in contrast to many cancers, the incidence of breast cancer was highest in the most socio-economically privileged areas, and this whatever the age of the patient. We have no explanation for this phenomenon, particularly with regard to the youngest age group of women. Finally, the aim of our fourth study, which is currently on-going, is to study at the individual level, using the new European deprivation index adapted to France, to what extent economic wealth and social standing, as well as the proximity of medical services for patients with breast cancer have an impact on tumour stage, access to treatment, treatment techniques and survival

Thesis (Ph. D.)--Florida State University, 2005.<br>Advisor: Dr. Fred W. Huffer, Florida State University, College of Arts and Sciences, Dept. of Statistics. Title and description from dissertation home page (viewed June 10, 2005). Document formatted into pages; contains xii, 130 pages. Includes bibliographical references.

The overall theme of this thesis focuses on methods for functional regression and nonlinear mixed-effects models with applications to PET data. The first part considers the problem of variable selection in regression models with functional responses and scalar predictors. We pose the function-on-scalar model as a multivariate regression problem and use group-MCP for variable selection. We account for residual covariance by "pre-whitening" using an estimate of the covariance matrix, and establish theoretical properties for the resulting estimator. We further develop an iterative algorithm that alternately updates the spline coefficients and covariance. Our method is illustrated by the application to two-dimensional planar reaching motions in a study of the effects of stroke severity on motor control. The second part introduces a functional data analytic approach for the estimation of the IRF, which is necessary for describing the binding behavior of the radiotracer. Virtually all existing methods have three common aspects: summarizing the entire IRF with a single scalar measure; modeling each subject separately; and the imposition of parametric restrictions on the IRF. In contrast, we propose a functional data analytic approach that regards each subject's IRF as the basic analysis unit, models multiple subjects simultaneously, and estimates the IRF nonparametrically. We pose our model as a linear mixed effect model in which shrinkage and roughness penalties are incorporated to enforce identifiability and smoothness of the estimated curves, respectively, while monotonicity and non-negativity constraints impose biological information on estimates. We illustrate this approach by applying it to clinical PET data. The third part discusses a nonlinear mixed-effects modeling approach for PET data analysis under the assumption of a compartment model. The traditional NLS estimators of the population parameters are applied in a two-stage analysis, which brings instability issue and neglects the variation in rate parameters. In contrast, we propose to estimate the rate parameters by fitting nonlinear mixed-effects (NLME) models, in which all the subjects are modeled simultaneously by allowing rate parameters to have random effects and population parameters can be estimated directly from the joint model. Simulations are conducted to compare the power of detecting group effect in both rate parameters and summarized measures of tests based on both NLS and NLME models. We apply our NLME approach to clinical PET data to illustrate the model building procedure.

Monitoring the performance of healthcare providers assists with maximising patient safety, maintaining quality control, and managing financial resources. However, such monitoring also attracts controversy, particularly when jurisdictions publish performance rankings, due to the effect on providers' reputations, referrals, and reimbursements for treatment. Thus, accurate and fair performance assessment is vital. The focus of this thesis is the performance of critical care providers in hospital intensive care units (ICUs). Patient mortality in hospital is the outcome that is monitored, and the standardised mortality ratio (SMR) is the performance indicator. Four inter-related methods of calculating SMRs are considered using a general multilevel model that contains patient- and provider-level attributes. Two options for the numerator of the SMR are either the observed mortalities or a smoothed version of the observed mortalities that allows for sampling variation. There are also two options for the denominator of the SMR, which represents the expected mortalities. The denominator adjusts for the patient casemix and either the actual or average provider attributes. This thesis presents the first known implementation of SMRs where the numerator is the smoothed observed mortalities, and both the numerator and denominator are based on a model containing (patient- and) provider-level attributes. The advantages and disadvantages of the four methods are discussed. The smoothed observed mortalities and the expected mortalities are defined in terms of intractable integrals. These integrals are evaluated numerically, often by adaptive quadrature. A much quicker but less accurate alternative is the Laplace approximation, and extending this technique may lead to a better compromise between speed and accuracy. In this thesis, the Laplace approximation is extended beyond that covered in the literature, and details are provided on how the integrals are expressible as series of any order. Comparisons against published results demonstrate that the newly developed extensions are much faster and almost as accurate as adaptive quadrature. The challenge of estimating SMR uncertainty is addressed by bootstrapping, and a non-parametric procedure is described for this purpose. Bootstrap procedures tend to be computationally intensive, which highlights a significant advantage of using extended versions of the Laplace approximation. The four variations of SMRs are calculated for a subset of the Australian and New Zealand Intensive Care Society (ANZICS) Adult Patient Database (APD). Deidentified patient records are voluntarily and retrospectively submitted to the APD by the majority of Australian and New Zealand adult ICUs. This thesis examines the in-hospital mortality data of 370,554 patient admissions to 170 ICUs between 2011 and 2015 inclusive. Risk-adjusted mortality generally decreased over time. Furthermore, risk-adjusted mortality was significantly higher for the ICUs of tertiary hospitals. This was re ected in the estimated SMRs when the expected mortalities were based on average ICU attributes. In this application, the smoothing of observed mortalities is recommended for the process of identifying unusually performing ICUs. There was also substantial variability in the estimated SMRs by each method. This was predominantly due to the variability within hospital types, and was largest for the ICUs of private hospitals.<br>Thesis (Ph.D.) -- University of Adelaide, School of Mathematical Sciences, 2020

This thesis consists of three essays that address various aspects of the economics of maternal health care. The first two essays examine the determinants of utilization of maternal health care services in low-income countries, while the third essay examines the determinants of utilization of prenatal ultrasonography in Canada. The first essay examines the influence of prenatal attendance (as well as a wide array of observed individual-, household- and community-level characteristics) on a woman’s decision to give birth at a health facility or at home for thirty-two low-income countries (across Asia, Sub-Saharan Africa and Latin America). This empirical investigation employs the Demographic and Health Surveys (DHS) data and a two-level random intercept model. The results show that prenatal attendance has a substantial influence on the use of facility delivery in all three geographical regions. Women having four prenatal visits were 7.3 times more likely to deliver at a health facility than those with no prenatal care. The second essay addresses two related questions: what factors determine a woman’s decision to seek prenatal care; and are those the same factors that determine the frequency of care? This investigation also utilizes Demographic and Health Surveys (DHS) data for thirty-two low-income countries (across Asia, Sub-Saharan Africa and Latin America) and applies a two-part and multi-level model to that data. The results suggest that, though a wide range of factors influence both decisions, that influence varies in magnitude across the two decisions, as well as across the three geographical regions. The third essay examines the influence of various socioeconomic and demographic factors on the frequency of prenatal ultrasounds in Canada, while controlling for maternal risk profiles. This investigation utilizes data from the Maternity Experience Survey (MES) of the Canadian Perinatal Surveillance System and employs a count data regression model (the Poisson distribution) to estimate the effect of various factors on the number of prenatal ultrasounds. The results of this investigation suggest that, even after controlling for maternal risk factors, the type of health-care provider, province of prenatal care, and timings of first ultrasound are the strongest predictors of number of ultrasounds.

Le contrôle des parlements nationaux envers les affaires européennes a récemment reçu beaucoup d’attention autant des institutions de l’Union européenne (UE) que des auteurs participant à la littérature sur le déficit démocratique. Pour autant, si plusieurs travaux ont démontré comment ce contrôle pouvait contribuer à améliorer la médiatisation des enjeux européens ou encore la transposition des directives, son rôle sur les attitudes des citoyens tient souvent du postulat et n’a jusqu’à présent fait l’objet d’aucune recherche. En mobilisant les données issues du projet Observatory of National Parliaments after Lisbon (OPAL) récoltées entre 2010 et 2012, cette étude adopte une méthodologie quantitative avec pour ambition de mesurer l’influence que le contrôle parlementaire des affaires européennes pourrait avoir dans la formation des attitudes envers l’UE. Étant donné que les attitudes envers le niveau national et européen sont étroitement reliées, nous avons en premier lieu démontré que le contrôle parlementaire participait à renforcer la confiance envers le parlement national. En ce qui concerne le niveau européen, nos résultats indiquent que le contrôle parlementaire semble avoir un effet antagoniste sur la confiance envers l’UE avec d’une part la capacité institutionnelle des parlements ayant un effet positif, et d’autre part l’activité parlementaire ayant un effet négatif. Cette recherche, bien qu’exploratoire et donc perfectible, pose ainsi les bases d’une meilleure compréhension du rôle que pourraient jouer les parlements nationaux dans la formation des attitudes envers l’UE.<br>The oversight of national parliaments over European affairs has recently received a great deal of attention, both from institutions of the European Union (EU) and from authors contributing to the literature on the democratic deficit. However, while several studies have shown how this control could contribute positively to the media coverage of European issues or to the transposition of directives, its role on citizens' attitudes is often postulated and has so far not been demonstrated. By mobilizing data from the Observatory of National Parliaments after Lisbon (OPAL) project collected between 2010 and 2012, this study adopts a quantitative methodology with the ambition of measuring the influence that parliamentary oversight over European affairs could have in shaping attitudes towards the EU. Since attitudes towards the national and European level are closely linked, I first demonstrated that parliamentary oversight helps to build confidence in the national parliament. Regarding the European level, the results indicate that parliamentary control seems to have an antagonistic effect on trust in the EU; on the one hand, the institutional capacity of parliaments have a positive effect, and on the other hand, the parliamentary activity has a negative effect. This research, although exploratory and therefore preliminary, thus lays the foundations for a better understanding of the role that national parliaments could potentially play in shaping attitudes towards the EU.

Women in Australia have gone from being under-represented to being over-represented in university education, but they are still far less likely than men to engage in mathematically intensive science fields including engineering, information technology and the physical sciences. With a rapid growth of employment opportunities in these fields, women need quantitative skills to become competitive in technologically and science-oriented niches of the labour market. The persisting gender gap in mathematically intensive fields is important also because it may reinforce the stereotypical belief that males are naturally more talented in mathematics, abstract thinking and technical problem solving. The prevalence of such a belief drives adolescents to aspire to gender-typical occupations and thus reproduces gender inequality. Given this, there is an urgent need to systematically examine the extent to which socialisation influences and educational experiences in adolescence affect the participation in advanced high school mathematics and mathematically intensive university qualifications. The key question to consider is why engagement in advanced mathematics and cognate disciplines remains so strongly segregated by gender. This thesis offers a comprehensive examination of this issue in Australia by drawing on the theories of gender stratification and educational psychology. The scope of this examination is broader than any other Australian study of this issue to date. I adopt a life course perspective to study the impact of teenage educational experiences and occupational expectations on the gender differences in later pursuits of advanced mathematics subjects in Year 12 and mathematically intensive fields at university. To achieve this, I use multilevel logistic regression models to analyse the data from the 2003 cohort of the Longitudinal Survey of Australian Youth. The data comprise a nationally representative sample of adolescents who turned 15 around 2003 and entered the labour market in the following decade. Occupational expectations are crucial in explaining why boys are considerably more likely than girls to enrol in advanced mathematics subjects in Year 12. These expectations, however, are less influential than the combined effect of self-assessed mathematical competence of students and their achievement in mathematics. The gender gap in Year 12 advanced mathematics enrolment would disappear completely should we succeed in generating the same levels of self-assessed mathematical competence and in fostering similar levels of early achievement in mathematics across both genders. To achieve gender parity in the choice of a mathematically intensive university major, we would also have to persuade teenagers of both genders to aspire to similar careers and have similar confidence in their mathematical abilities. Apart from individual micro-social characteristics of students, single-sex schooling enhances the participation of girls in advanced high school mathematics and related fields of study at university. The advantage of all-girls education is evident in these analyses even after considering the pre-existing differences between single-sex and coeducational schools in school resources, teacher quality and the policy of selectivity in student admissions. These results suggest that all-girls secondary education provides an environment that somewhat counters gender stereotypes and fosters mathematically intensive studies, not only in high school but also at university.

Problématique : L’amélioration de l’accessibilité financière aux soins de santé est essentielle pour réduire la morbidité et de la mortalité infantile dans les pays à ressources limitées. Cependant, les preuves disponibles sur la relation entre un accès accru aux soins et l’amélioration la santé infantile, dans le long terme, demeurent insuffisantes et parfois inconnues. Dans le contexte spécifique de la région du Sahel au Burkina Faso où les niveaux élevés de morbidité et de malnutrition coïncident avec un faible recours aux soins, une intervention de santé publique associant la gratuité des soins à l’amélioration de la qualité des soins et à la prise en charge de la malnutrition dans la communauté a été mise en œuvre en septembre 2008. Objectifs : En utilisant des approches statistiques et épidémiologiques appliquées aux données transversales et de séries chronologiques, cette thèse vise à apporter une meilleure compréhension de la façon dont la présence de l’intervention dans les communautés peut augmenter et maintenir l’utilisation des services de santé à long terme et améliorer la santé des enfants de moins de cinq ans. Les objectifs spécifiques sont : 1) évaluer le maintien à long terme des effets de l’intervention sur l’utilisation des services de santé chez les enfants de moins de cinq ans, 2) évaluer l’effet contextuel de l’intervention, quatre ans après le début de sa mise en œuvre, sur la probabilité de survenue d’une maladie et sur la probabilité d’utilisation des services de santé chez les enfants de moins de cinq ans, et 3) évaluer l’effet contextuel de l’intervention, quatre ans après le début de sa mise en œuvre, sur le retard de croissance chez les enfants de moins de cinq ans. Méthodes : Les données proviennent du système national d’information sanitaire, d’une enquête rétrospective sur les services de santé ainsi que d’une enquête de ménages réalisée quatre ans après le début de l’intervention dans 41 villages du district d’intervention et 51 villages du district de comparaison. Nous avons utilisé un plan quasi expérimental à séries temporelles interrompues avec groupe de comparaison pour évaluer les effets immédiats et à long terme de l’intervention sur les taux d’utilisation des services de santé. Ensuite, un plan d’étude transversale post-intervention avec un groupe de comparaison nous a permis d’évaluer l’effet contextuel de l’intervention sur la probabilité de survenue d’une maladie, sur la probabilité d’utilisation des services de santé et sur le retard de croissance chez les enfants de moins de cinq ans. La stratégie analytique a combiné la méthode de pondération par les scores de propension pour équilibrer les covariables entre les deux groupes, la modélisation binomiale négative à effets mixtes, les régressions linéaire et logistique multiniveaux. Résultats : L’intervention de gratuité des soins associée à l’amélioration de la qualité des soins et à la prise en charge de la malnutrition dans la communauté était associée à l’augmentation et au maintien de l’utilisation des services de santé au-delà de quatre ans (ratio des taux d’incidence = 2,33 ; IC 95 % = 1,98 – 2,67). En outre, comparativement aux enfants vivant dans le district de contrôle, la probabilité d’utiliser les services de santé était de 17,2 % plus élevée chez les enfants vivant dans le district d’intervention (IC 95 % = 15,01–26,6) ; et de 20,7 % plus élevée lorsque l’épisode de maladie était sévère (IC 95 % = 9,9–31,5). Ces associations étaient significatives, quels que soient la distance par rapport aux centres de santé et le statut socio-économique du ménage. Par ailleurs, alors que le contexte de résidence expliquait 9,36 % de la variance du retard de croissance (corrélation intraclasse = 9,36 % ; IC 95 % = 6,45–13,38), la présence de l’intervention dans les villages n’explique que 2 % de la variance du retard de croissance. Cependant, nous n’avons pas pu démontrer que la présence de l’intervention dans les communautés était associée à une réduction de la probabilité de survenue d’un épisode de maladie (Différentiel des probabilités = 4.4 ; IC 95% = -1.0 – 9.8), ni à une amélioration significative de l’état nutritionnel des enfants de moins de cinq ans (RC = 1,13 ; IC 95 % = 0,83–1,54). Conclusion : Cette thèse souligne que la gratuité des soins associée à l’amélioration de la qualité des soins et à la prise en charge de la malnutrition dans la communauté est efficace pour augmenter et maintenir l’utilisation des services de santé et réduire les inégalités géographiques de recours aux soins. Cependant, cette intervention n’était pas associée à une amélioration des résultats de santé infantile. Bien que des études longitudinales rigoureuses soient nécessaires pour comprendre pleinement l’influence potentielle de cette intervention sur la morbidité, cette thèse plaide pour la nécessité d’agir simultanément sur les autres déterminants sociaux de la santé et d’intégrer, de manière synergique, des interventions spécifiques à la nutrition pour plus d’impact sur la santé infantile.<br>Introduction: Improving financial access to health care is believed to be essential for reducing the burden of child morbidity and mortality in resource-limited settings, but the available evidence on the relationship between increased access and health remains scarce and the long-term issues are still unknown. In the specific context of the Sahel region in Burkina Faso where high levels of morbidity and malnutrition coincide with low health care use, a pilot intervention for free health care including quality of care improvement and management of malnutrition at the community level was implemented in September 2008. Objectives: Using statistical and epidemiological approaches applied to cross-sectional and time series data, this thesis aims to provide a better understanding of how the presence of intervention in communities can increase and maintain long-term use of health services and improve the health of children under five years. The specific objectives are: 1) to evaluate the long-term effects of the intervention on the use of health services in children under the age of five, 2) to estimate the contextual effect of intervention on the probability of occurrence of and the likelihood of health services being used by children under five, four years after the start of its implementation, and 3) to evaluate the contextual effect of the intervention on stunting in children under five, four years after the start of its implementation. Methods: The data for the analyses were provided from a variety of sources including the national health information system, a retrospective health services survey, and a household survey conducted four years after the intervention onset in 41 villages in the intervention district and 51 villages in the comparison district. We used a quasi-experimental controlled interrupted time-series design group to analyze the immediate and long-term effects of the intervention on the rate of health services utilization in children under five. Then, a quasi-experimental post-test-only design that included a control group allowed us to evaluate the contextual effect of the intervention on the probability of occurrence of a disease, on the probability of use of health services, and stunting in children under five. The analytic strategy combined the propensity score weighting method to balance the covariates between the two groups, two-level mixed-effects negative binomial, and linear and logistic regression models to account for the hierarchical structure of data. Results: The intervention for free health care including quality of care improvement and management of malnutrition at the community level was associated with an increased and maintained use of health services beyond four years after the onset of intervention (incidence rate ratio = 2.33; 95% CI = 1.98–2.67). In addition, compared to children living in the comparison district, the probability of using health services was 17.2% higher among those living in the intervention district (95% CI = 15.0–26.6); and 20.7% higher when the illness episode was severe (95% CI = 9.9–31.5). These associations were significant regardless of the distance to health centers and the socio-economic status of households. In addition, inequalities in the use of care were less pronounced in the intervention villages compared to those in the control village. Finally, the results also showed that the residence context accounted for 9.36% of the variance in stunting (intra-class correlation = 9.36% ; 95% CI = 6.45–13.38), and only 2% of the variance in stunting was explained by the intervention. However, we could not demonstrate that the intervention in these communities was associated with a reduced probability of an illness occurring (AME=4.4 (95% CI: -1.0 – 9.8), nor with a significant improvement in the nutritional status among children under five (OR = 1.13; 95% CI = 0.83–1.54). Conclusion: This thesis underlines the importance that affordable health care, including quality of care, as well as improving the management of malnutrition at the community level, are effective in increasing and maintaining the use of health services and reduce geographical inequalities in the use of care. However, this intervention was not associated with improved child health outcomes. Although rigorous longitudinal studies are necessary to fully understand the potential influence of this intervention on morbidity, this thesis highlights the need to simultaneously act on other social determinants of health and to synergistically integrate nutrition-specific interventions for greater impact on child health.