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Statistical methods for causal inference in cohort studies with longitudinal data : applications to aging
No full textL’épidémiologie du vieillissement pose de nombreux problèmes méthodologiques ayant mené au développement de modèles statistiques adaptés. Toutefois, la recherche de facteurs impactant de façon causale le processus de vieillissement dans les études de cohorte observationnelles ainsi que la compréhension des voies d’action causales de ces facteurs restent encore limitées par la rareté voire l’absence de méthodes d’inférence causale adaptées aux données longitudinales. Cette thèse vise à développer de nouveaux outils d’inférence causale pour l’étude des facteurs de risque du vieillissement et des mécanismes sous-jacents dans les études observationnelles longitudinales. Dans une première partie, nous nous sommes intéressés aux méthodes d’analyse de médiation permettant de décomposer les effets totaux entre un facteur de risque et une maladie, en un effet direct et des effets indirects passant par des variables médiatrices. Plus précisément, nous avons proposé une approche d’analyse de médiation pour étudier le lien causal entre une exposition fixe dans le temps et des processus de médiation, de confusion et d’outcome final, tous les trois définis en temps continu mais mesurés de façon irrégulière au cours du temps. pour le médiateur et l’outcome. Nous avons également discuté une approche d’analyse de médiation permettant d’étudier des variables intermédiaires et terminales de type temps d’événement, avec une possible censure par intervalle du temps d’événement intermédiaire. Dans la deuxième partie, nous avons étendu la méthode par variables instrumentales pour traiter la confusion non observée lorsque l’on étudie une exposition fixe dans le temps et un outcome mesuré de façon répétée dans le temps. Nous avons appliqué ces approches aux données de la cohorte populationnelle 3C, s’interessant au processus de vieillissement cérébral chez les personnes âgées. Les travaux présentés dans cette thèse ouvrent ainsi la voie à une meilleure compréhension des mécanismes causaux impliqués dans diverses pathologies, en présence de phénomènes d’intérêt évoluant au cours du temps.The field of aging epidemiology poses numerous statistical challenges that have led to the development of adapted statistical models. However, the search for factors impacting the aging process causally in observational cohort studies, as well as the understanding of the causal pathways of these factors, is still limited by the rarity or even absence of causal inference methods adapted to longitudinal data. This thesis aims to develop new causal inference tools for studying aging risk factors and underlying mechanisms in longitudinal observational studies. In the first part, we focused on mediation analysis methods to decompose total effects between a risk factor and a disease into a direct effect and indirect effects through intermediate variables. More specifically, we proposed a mediation analysis approach to study the causal link between a fixed exposure over time and mediator, confounder and outcome all defined in continuous time but measured irregularly over time. We also discussed a mediation analysis approach to study intermediate and terminal time-to-event variables, with possible interval censoring of the intermediate time-to-event. In the second part, we extended the instrumental variables method to address unobserved confounding when studying a time-fixed exposure and an outcome measured repeatedly over time. We applied these approaches to data from the 3C population cohort, focusing on the process of cerebral aging in the elderly. The work presented in this thesis thus paves the way for a better understanding of the causal mechanisms involved in various pathologies, in presence of health phenomena evolving over time
Méthodes statistiques pour l’inférence causale dans les études de cohortes en présence de données longitudinales : applications au vieillissement
No full textThe field of aging epidemiology poses numerous statistical challenges that have led to the development of adapted statistical models. However, the search for factors impacting the aging process causally in observational cohort studies, as well as the understanding of the causal pathways of these factors, is still limited by the rarity or even absence of causal inference methods adapted to longitudinal data. This thesis aims to develop new causal inference tools for studying aging risk factors and underlying mechanisms in longitudinal observational studies. In the first part, we focused on mediation analysis methods to decompose total effects between a risk factor and a disease into a direct effect and indirect effects through intermediate variables. More specifically, we proposed a mediation analysis approach to study the causal link between a fixed exposure over time and mediator, confounder and outcome all defined in continuous time but measured irregularly over time. We also discussed a mediation analysis approach to study intermediate and terminal time-to-event variables, with possible interval censoring of the intermediate time-to-event. In the second part, we extended the instrumental variables method to address unobserved confounding when studying a time-fixed exposure and an outcome measured repeatedly over time. We applied these approaches to data from the 3C population cohort, focusing on the process of cerebral aging in the elderly. The work presented in this thesis thus paves the way for a better understanding of the causal mechanisms involved in various pathologies, in presence of health phenomena evolving over time.L’épidémiologie du vieillissement pose de nombreux problèmes méthodologiques ayant mené au développement de modèles statistiques adaptés. Toutefois, la recherche de facteurs impactant de façon causale le processus de vieillissement dans les études de cohorte observationnelles ainsi que la compréhension des voies d’action causales de ces facteurs restent encore limitées par la rareté voire l’absence de méthodes d’inférence causale adaptées aux données longitudinales. Cette thèse vise à développer de nouveaux outils d’inférence causale pour l’étude des facteurs de risque du vieillissement et des mécanismes sous-jacents dans les études observationnelles longitudinales. Dans une première partie, nous nous sommes intéressés aux méthodes d’analyse de médiation permettant de décomposer les effets totaux entre un facteur de risque et une maladie, en un effet direct et des effets indirects passant par des variables médiatrices. Plus précisément, nous avons proposé une approche d’analyse de médiation pour étudier le lien causal entre une exposition fixe dans le temps et des processus de médiation, de confusion et d’outcome final, tous les trois définis en temps continu mais mesurés de façon irrégulière au cours du temps. pour le médiateur et l’outcome. Nous avons également discuté une approche d’analyse de médiation permettant d’étudier des variables intermédiaires et terminales de type temps d’événement, avec une possible censure par intervalle du temps d’événement intermédiaire. Dans la deuxième partie, nous avons étendu la méthode par variables instrumentales pour traiter la confusion non observée lorsque l’on étudie une exposition fixe dans le temps et un outcome mesuré de façon répétée dans le temps. Nous avons appliqué ces approches aux données de la cohorte populationnelle 3C, s’interessant au processus de vieillissement cérébral chez les personnes âgées. Les travaux présentés dans cette thèse ouvrent ainsi la voie à une meilleure compréhension des mécanismes causaux impliqués dans diverses pathologies, en présence de phénomènes d’intérêt évoluant au cours du temps
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Biometrics
No full textMediation analysis aims to decipher the underlying causal mechanisms between an exposure, an outcome, and intermediate variables called mediators. Initially developed for fixed-time mediator and outcome, it has been extended to the framework of longitudinal data by discretizing the assessment times of mediator and outcome. Yet, processes in play in longitudinal studies are usually defined in continuous time and measured at irregular and subject-specific visits. This is the case in dementia research when cerebral and cognitive changes measured at planned visits in cohorts are of interest. We thus propose a methodology to estimate the causal mechanisms between a time-fixed exposure (), a mediator process (), and an outcome process () both measured repeatedly over time in the presence of a time-dependent confounding process (). We consider 2 types of causal estimands, the natural effects and path-specific effects. We provide identifiability assumptions, and we employ a multivariate mixed model based on differential equations for their estimation. The performances of the method are assessed in simulations, and the method is illustrated in 2 real-world examples motivated by the 3C cerebral aging study to assess (1) the effect of educational level on functional dependency through depressive symptomatology and cognitive functioning and (2) the effect of a genetic factor on cognitive functioning potentially mediated by vascular brain lesions and confounded by neurodegeneration
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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