Submitted by Renato Alexandre Scott Filho (renatoascottf@gmail.com) on 2015-02-24T23:39:19Z No. of bitstreams: 1 2015_02_22_RASF_Efeito da eleição do candidato da oposição sobre a apresentação e aprovação de projetos do prefeito na câmara.pdf: 2561359 bytes, checksum: 95f0e7dadd28a3c61c44fbfb388fccae (MD5) / Approved for entry into archive by Renata de Souza Nascimento (renata.souza@fgv.br) on 2015-02-25T00:25:39Z (GMT) No. of bitstreams: 1 2015_02_22_RASF_Efeito da eleição do candidato da oposição sobre a apresentação e aprovação de projetos do prefeito na câmara.pdf: 2561359 bytes, checksum: 95f0e7dadd28a3c61c44fbfb388fccae (MD5) / Made available in DSpace on 2015-02-25T14:51:20Z (GMT). No. of bitstreams: 1 2015_02_22_RASF_Efeito da eleição do candidato da oposição sobre a apresentação e aprovação de projetos do prefeito na câmara.pdf: 2561359 bytes, checksum: 95f0e7dadd28a3c61c44fbfb388fccae (MD5) Previous issue date: 2015-02-05 / This study aims to analyze the effect of a challenger winning the municipal elections on the presentation and approval by the city council of projects proposed by the then elected mayor, on the subsequent year. This subject relates to the advantage citizens take when they choose the alternation of power option instead of the reelection one, as well as to the relation between the new chief of the executive and the city councilmen. A bound is then established with an electoral literature that excels at the analysis of factors leading to the reelection of a politician, but that may well be deepened on the examination of the future consequences of the alternation of power. In a similar way, a contribution is made by the provision of an econometrical toolset to the theoretical analyses of executive-legislative relations in the local level. The employed methodology is based on the application of the regression discontinuity design technique (or RDD) to data collected from the Brazilian Supreme Electoral Court and from a 2005’s legislative census. Following the data examination, and with moderate significance, it is argued that when the challenger is elected mayor he tends to propose less projects in the first year of his term (as opposed to the incumbent mayor), but these projects, on the other hand, get a proportionally more favorable reception by the city council. / Este trabalho tem por objetivo analisar o efeito de se eleger um candidato da oposição em eleições municipais sobre a apresentação e aprovação de projetos do prefeito então eleito na câmara de vereadores, no ano subsequente. Tal questão diz respeito à vantagem, para os munícipes, de optar pela alternância de poder em detrimento da reeleição, bem como à relação entre o novo representante do executivo e os vereadores. Dialoga-se, assim, com uma literatura político-eleitoral pródiga na análise dos fatores que favorecem a reeleição, mas que pouco se debruçou sobre as consequências futuras da alternância de poder. Igualmente, contribui-se com um embasamento econométrico para as discussões fomentadas a nível teórico a respeito das relações entre os poderes no município. A metodologia empregada se baseia na técnica de regressões descontínuas ou RDD para tratamento quase-experimental dos dados coletados no TSE e no Censo Legislativo de 2005. A partir da análise dos dados, e com significância moderada, argumenta-se que quando o prefeito eleito é da oposição ele tende a apresentar menos projetos à câmara em seu primeiro ano de mandato, mas recebe acolhida proporcionalmente mais favorável por parte dos vereadores.

Les levures du genre Candida figurent parmi les pathogènes majeurs isolés chez les patients en soins intensifs et sont responsables d'infections systémiques : les candidoses invasives. Le retard et le manque de fiabilité du diagnostic sont susceptibles d'aggraver l'état du patient et d'augmenter le risque de décès à court terme. Pour respecter les objectifs de traitement, les experts recommandent de traiter le plus précocement possible les patients à haut risque de candidose invasive. Cette attitude permet de proposer un traitement précoce aux malades atteints, mais peut entraîner un traitement inutile et coûteux et favoriser l'émergence de souches de moindre sensibilité aux antifongiques utilisés.Ce travail applique des méthodes statistiques modernes à des données observationnelles longitudinales. Il étudie l'impact des traitements antifongiques systémiques sur la répartition des quatre principales espèces de Candida dans les différents prélèvements de patients en réanimation médicale, sur leur sensibilité à ces antifongiques, sur le diagnostic des candidémies ainsi que sur le pronostic des patients. Les analyses de séries de données temporelles à l'aide de modèles ARIMA (moyenne mobile autorégressive intégrée) ont confirmé l'impact négatif de l'utilisation des antifongiques sur la sensibilité des principales espèces de Candida ainsi que la modification de leur répartition sur une période de dix ans. L'utilisation de modèles hiérarchiques sur données répétées a montré que le traitement influence négativement la détection des levures et augmente le délai de positivité des hémocultures dans le diagnostic des candidémies. Enfin, l'utilisation des méthodes d'inférence causale a montré qu'un traitement antifongique préventif n'a pas d'impact sur le pronostic des patients non neutropéniques, non transplantés et qu'il est possible de commencer une désescalade précoce du traitement antifongique entre le premier et le cinquième jour après son initiation sans aggraver le pronostic. / Candida species are among the main pathogens isolated from patients in intensive care units (ICUs) and are responsible for a serious systemic infection: invasive candidiasis. A late and unreliable diagnosis of invasive candidiasis aggravates the patient's status and increases the risk of short-term death. The current guidelines recommend an early treatment of patients with high risks of invasive candidiasis, even in absence of documented fungal infection. However, increased antifungal drug consumption is correlated with increased costs and the emergence of drug resistance whereas there is yet no consensus about the benefits of the probabilistic antifungal treatment.The present work used modern statistical methods on longitudinal observational data. It investigated the impact of systemic antifungal treatment (SAT) on the distribution of the four Candida species most frequently isolated from ICU patients', their susceptibilities to SATs, the diagnosis of candidemia, and the prognosis of ICU patients. The use of autoregressive integrated moving average (ARIMA) models for time series confirmed the negative impact of SAT use on the susceptibilities of the four Candida species and on their relative distribution over a ten-year period. Hierarchical models for repeated measures showed that SAT has a negative impact on the diagnosis of candidemia: it decreases the rate of positive blood cultures and increases the time to positivity of these cultures. Finally, the use of causal inference models showed that early SAT has no impact on non-neutropenic, non-transplanted patient prognosis and that SAT de-escalation within 5 days after its initiation in critically ill patients is safe and does not influence the prognosis.

Le sentiment d’agentivité est défini comme le sentiment de contrôler nos actions, et à travers elles, les évènements du monde extérieur. Cet ensemble phénoménologique dépend de notre capacité d’apprendre les contingences entre nos actions et leurs résultats, et un algorithme classique pour modéliser cela vient du domaine de l’apprentissage par renforcement. Dans cette thèse, nous avons utilisé l’approche de modélisation cognitive pour étudier l’interaction entre agentivité et apprentissage par renforcement. Tout d’abord, les participants réalisant une tâche d’apprentissage par renforcement tendent à avoir plus d’agentivité. Cet effet est logique, étant donné que l’apprentissage par renforcement consiste à associer une action volontaire et sa conséquence. Mais nous avons aussi découvert que l’agentivité influence l’apprentissage de deux manières. Le mode par défaut pour apprendre des contingences action-conséquence est que nos actions ont toujours un pouvoir causal. De plus, simplement choisir une action change l’apprentissage de sa conséquence. En conclusion, l’agentivité et l’apprentissage par renforcement, deux piliers de la psychologie humaine, sont fortement liés. Contrairement à des ordinateurs, les humains veulent être en contrôle, et faire les bons choix, ce qui biaise notre aquisition d’information. / Sense of agency or subjective control can be defined by the feeling that we control our actions, and through them effects in the outside world. This cluster of experiences depend on the ability to learn action-outcome contingencies and a more classical algorithm to model this originates in the field of human reinforcementlearning. In this PhD thesis, we used the cognitive modeling approach to investigate further the interaction between perceived control and reinforcement learning. First, we saw that participants undergoing a reinforcement-learning task experienced higher agency; this influence of reinforcement learning on agency comes as no surprise, because reinforcement learning relies on linking a voluntary action and its outcome. But our results also suggest that agency influences reinforcement learning in two ways. We found that people learn actionoutcome contingencies based on a default assumption: their actions make a difference to the world. Finally, we also found that the mere fact of choosing freely shapes the learning processes following that decision. Our general conclusion is that agency and reinforcement learning, two fundamental fields of human psychology, are deeply intertwined. Contrary to machines, humans do care about being in control, or about making the right choice, and this results in integrating information in a one-sided way.

Background: When assessing the association between a factor X and a subsequent outcome Y in observational studies, the question that arises is what are the variables to adjust for to reduce bias due to confounding for causal inference on the effect of X on Y. Disregarding such factors is often a source of overestimation because these variables may affect both X and Y. On the other hand, adjustment for such variables can also be a source of underestimation because such variables may be the causal consequence of X and part of the mechanism that leads from X to Y. Methods: In this paper, we present a simple method to compute control variables in the presence of age at onset data on both X and a set of other variables. Using these age at onset data, control variables are computed that adjust only for conditions that occur prior to X. This strategy can be used in prospective as well as in survival analysis. Our method is motivated by an argument based on the counterfactual model of a causal effect. Results: The procedure is exemplified by examining of the relation between panic attack and the subsequent incidence of MDD. Conclusions: The results reveal that the adjustment for all other variables, irrespective of their temporal relation to X, can yield a false negative result (despite unconsidered confounders and other sources of bias).

Dans ce mémoire par articles, nous nous intéressons à l’apprentissage de modèles causaux à partir de données. L’intérêt de cette entreprise est d’obtenir une meilleure compréhension des données et de pouvoir prédire l’effet qu’aura un changement sur certaines variables d’un système étudié. Comme la découverte de liens causaux est fondamentale en sciences, les méthodes permettant l’apprentissage de modèles causaux peuvent avoir des applications dans une pléthore de domaines scientifiques, dont la génomique, la biologie et l’économie. Nous présentons deux nouvelles méthodes qui ont la particularité d’être des méthodes non-linéaires d’apprentissage de modèles causaux qui sont posées sous forme d’un problème d’optimisation continue sous contrainte. Auparavant, les méthodes d’apprentissage de mo- dèles causaux abordaient le problème de recherche de graphes en utilisant des stratégies de recherche voraces. Récemment, l’introduction d’une contrainte d’acyclicité a permis d’abor- der le problème différemment. Dans un premier article, nous présentons une de ces méthodes: GraN-DAG. Sous cer- taines hypothèses, GraN-DAG permet d’apprendre des graphes causaux à partir de données observationnelles. Depuis la publication du premier article, plusieurs méthodes alternatives ont été proposées par la communauté pour apprendre des graphes causaux en posant aussi le problème sous forme d’optimisation continue avec contrainte. Cependant, aucune de ces méthodes ne supportent les données interventionnelles. Pourtant, les interventions réduisent le problème d’identifiabilité et permettent donc l’utilisation d’architectures neuronales plus expressives. Dans le second article, nous présentons une autre méthode, DCDI, qui a la particularité de pouvoir utiliser des données avec différents types d’interventions. Comme le problème d’identifiabilité est moins important, une des deux instanciations de DCDI est un approximateur de densité universel. Pour les deux méthodes proposées, nous montrons que ces méthodes ont de très bonnes performances sur des données synthétiques et réelles comparativement aux méthodes traditionelles. / In this thesis by articles, we study the learning of causal models from data. The goal of this entreprise is to gain a better understanding of data and to be able to predict the effect of a change on some variables of a given system. Since discovering causal relationships is fundamental in science, causal structure learning methods have applications in many fields that range from genomics, biology, and economy. We present two new methods that have the particularity of being non-linear methods learning causal models casted as a continuous optimization problem subject to a constraint. Previously, causal strutural methods addressed this search problem by using greedy search heuristics. Recently, a new continuous acyclity constraint has allowed to address the problem differently. In the first article, we present one of these non-linear method: GraN-DAG. Under some assumptions, GraN-DAG can learn a causal graph from observational data. Since the publi- cation of this first article, several alternatives methods have been proposed by the community by using the same continuous-constrained optimization formulation. However, none of these methods support interventional data. Nevertheless, interventions reduce the identifiability problem and allow the use of more expressive neural architectures. In the second article, we present another method, DCDI, that has the particularity to leverage data with several kinds of interventions. Since the identifiabiliy issue is less severe, one of the two instantia- tions of DCDI is a universal density approximator. For both methods, we show that these methods have really good performances on synthetic and real-world tasks comparatively to other classical methods.

<p>Functional impairment is increasingly prevalent among middle-aged and older adults, with 2 in 5 adults over the age of 65 having some form of disability, the majority being limitations on mobility. Many older adults are able to maintain functional capacity well into later life, but the factors that contribute to high levels of function and the mechanisms by which they operate are unclear, although prior work has demonstrated the importance of social relationships for health. Guided by principles from the life course perspective and perspectives on social connectedness, this dissertation examined the role of social connectedness across the life course as a predictor of functional capacity in adulthood. I used existing longitudinal data from the national Midlife in the United States (MIDUS) study to pursue three central aims.</p> <p><br></p> <p>First, Paper 1 compared theoretical and data-driven approaches to classifying life course relationships, including multiple dimensions of social connectedness at different time points across the life course. Results showed that the data-driven approach (i.e., latent profile analysis) was a stronger predictor of functional limitations than the theoretical approach and revealed relationship trajectories consistent with life course cumulative processes. Second, using the profiles obtained from Paper 1, Paper 2 probed the association between life-course social connectedness and functional limitations by examining the potential mediating role of candidate biological and behavioral mechanisms, and moderation by socioeconomic status (SES). Paper 2 findings suggested that observed differences in later-life functional limitations based on life-course social connectedness can be at least partially explained by physical activity, but do not vary by SES. Contrary to hypotheses, inflammation was not a significant mediator. Third, Paper 3 used monozygotic twin data and within-family analyses to sharpen the focus on potential causal associations between life-course social connectedness and adult functional status. Results suggested that the association is likely driven by genetic and/or shared environmental influences. </p> <p><br></p> <p>Taken together, these results add to our understanding of social connectedness and health and address important gaps in the literature. These findings are used to generate theory- and intervention-relevant insights into the successful maintenance of health, independence, and function across the lifespan.</p>

La randomisation mendélienne est une méthode d’instrumentation utilisant des instruments de nature génétique afin d’estimer, via par exemple la régression des moindres carrés en deux étapes, une relation de causalité entre un facteur d’exposition et une réponse lorsque celle-ci est confondue par une ou plusieurs variables de confusion non mesurées. La randomisation mendélienne est en mesure de gérer le biais de confusion à condition que les instruments utilisés soient valides, c’est-à-dire qu’ils respectent trois hypothèses clés. On peut généralement se convaincre que deux des trois hypothèses sont satisfaites alors qu’un phénomène génétique, la pléiotropie, peut parfois rendre la troisième hypothèse invalide. En présence d’invalidité, l’estimation de l’effet causal de l’exposition sur la réponse peut être sévèrement biaisée. Afin d’évaluer la potentielle présence d’invalidité lorsqu’un seul instrument est utilisé, Glymour et al. (2012) ont proposé une méthode qu’on dénomme ici l’approche de la différence simple qui utilise le signe de la différence entre l’estimateur des moindres carrés ordinaires de la réponse sur l’exposition et l’estimateur des moindres carrés en deux étapes calculé à partir de l’instrument pour juger de l’invalidité de l’instrument. Ce mémoire introduit trois méthodes qui s’inspirent de cette approche, mais qui sont applicables à la randomisation mendélienne à instruments multiples. D’abord, on introduit l’approche de la différence globale, une simple généralisation de l’approche de la différence simple au cas des instruments multiples qui a comme objectif de détecter si un ou plusieurs instruments utilisés sont invalides. Ensuite, on introduit les approches des différences individuelles et des différences groupées, deux méthodes qui généralisent les outils de détection de l’invalidité de l’approche de la différence simple afin d’identifier des instruments potentiellement problématiques et proposent une nouvelle estimation de l’effet causal de l’exposition sur la réponse. L’évaluation des méthodes passe par une étude théorique de l’impact de l’invalidité sur la convergence des estimateurs des moindres carrés ordinaires et des moindres carrés en deux étapes et une simulation qui compare la précision des estimateurs résultant des différentes méthodes et leur capacité à détecter l’invalidité des instruments. / Mendelian randomization is an instrumentation method that uses genetic instruments to estimate, via two-stage least squares regression for example, a causal relationship between an exposure and an outcome when the relationship is confounded by one or more unmeasured confounders. Mendelian randomization can handle confounding bias provided that the instruments are valid, i.e., that they meet three key assumptions. While two of the three assumptions can usually be satisfied, the third assumption is often invalidated by a genetic phenomenon called pleiotropy. In the presence of invalid instruments, the estimate of the causal effect of exposure on the outcome may be severely biased. To assess the potential presence of an invalid instrument in single-instrument studies, Glymour et al. (2012) proposed a method, hereinafter referred to as the simple difference approach, which uses the sign of the difference between the ordinary least squares estimator of the outcome on the exposure and the two-stage least squares estimator calculated using the instrument. Based on this approach, we introduce three methods applicable to Mendelian randomization with multiple instruments. The first method is the global difference approach and corresponds to a simple generalization of the simple difference approach to the case of multiple instruments that aims to detect whether one or more instruments are invalid. Next, we introduce the individual differences and the grouped differences approaches, two methods that generalize the simple difference approach to identify potentially invalid instruments and provide new estimates of the causal effect of the exposure on the outcome. The methods are evaluated using a theoretical investigation of the impact that invalid instruments have on the convergence of the ordinary least squares and two-stage least squares estimators as well as with a simulation study that compares the accuracy of the respective estimators and the ability of the corresponding methods to detect invalid instruments.

[pt] Esta dissertação tem por objetivo apresentar os resultados da pesquisa de mestrado em que se procurou evidenciar algumas características da relação de David Hume com a indução. Segundo a interpretação corrente, Hume é o responsável por mostrar que nossa razão não é capaz de justificar qualquer um de nossos raciocínios indutivos. O problema de Hume também se caracteriza por ser um problema acerca da racionalidade da ciência, pois se seu método principal, a indução, não pode receber suporte racional, parece lícito afirmar que o resultado de uma inferência indutiva é irracional. A fim de delinear o campo exato em que se insere a crítica humeana, este texto irá mostrar como Hume apresenta suas teorias acerca do raciocínio causal em seu Tratado da natureza humana, traçar as características exatas do raciocínio causal de Hume e confrontá-las com as formas de interpretação presentes em alguns de seus principais comentadores. Procuramos tornar claras as falhas apresentadas nestas interpretações. Em seguida trataremos de discutir algumas das mais celebradas interpretações da filosofia de Hume, centrando nossa análise nos textos de Mackie, Beauchamp e Mappes. O capítulo final tem por objetivo mostrar as características racionais que podem ser atribuídas aos raciocínios causais humeanos, salientando o caráter particular de suas inferências. Finalizando, mostraremos como a origem do princípio da cópia pode ser um exemplo do uso de inferências indutivas por parte de Hume, o que nos leva a considerações heterodoxas a respeito de sua visão a respeito da racionalidade. / [en] The aim of this work is to present the results of my master´s degree research, which tried to show some of the characteristics of David Hume´s approach to induction. According to the standard interpretation, Hume is responsible for showing that our reason is not able to justify any of our inductive reasonings. Hume´s problem also characterizes itself by being a problem about the rationality of science, for, since his main method, induction, cannot receive a rational foundation, it seems licit to assert that the result of any inductive inference is irrational. In order to precisely describe the Humean criticism I am going to show how Hume presents his theories concerning causal reasoning in this A Treatise of Human Nature, define the exact characteristics of causal reasoning according to him, and compare this analysis to those by some of his main critics. We shall try to bring to light the proposed inadequacy of the latter. Next we will discuss some of the most celebrated interpretations of Hume´s philosophy, specially those by of Mackie, Beauchamp and Mappes. The final chapter aims at showing the rational characteristics that can be assigned to Humean causal reasoning emphasizing the particular character of his inferences. Finally, we show how the origin of the copy principle can be an instance of the use of inductive inferences by Hume, which allows us to risk some heterodox hypotheses concerning his view of rationality.

Les essais cliniques randomisés (ECRs) constituent la meilleure solution pour obtenir des effets causaux et évaluer l’efficacité des médicaments. Toutefois, vu qu’ils ne sont pas toujours réalisables, les bases de données administratives servent de solution de remplacement. Le sujet principal de cette thèse peut être divisée en deux parties, le tout, repartie en trois articles. La première partie de cette thèse traite de l’utilisation des estimateurs doublement robustes en inférence causale sur des bases de données administratives avec intégration des méthodes d’apprentissage automatique. Nous pouvons citer, par exemple, l’estimateur par maximum de vraisemblance ciblé (TMLE) et l’estimateur par augmentation de l’inverse de la probabilité de traitement (AIPTW). Ces méthodes sont de plus en plus utilisées en pharmaco-épidémiologie pour l’estimation des paramètres causaux, comme l’effet moyen du traitement. Dans la deuxième partie de cette thèse, nous développons un estimateur doublement robuste pour les données administratives et nous étendons une méthode existante pour l’ajustement du biais de sélection utilisant un échantillon probabiliste de référence. Le premier manuscrit de cette thèse présente un outil de diagnostic pour les analystes lors de l’utilisation des méthodes doublement robustes. Ce manuscrit démontre à l’aide d’une étude de simulation l’impact de l’estimation du score de propension par des méthodes flexibles sur l’effet moyen du traitement, et ce, en absence de positivité pratique. L’article propose un outil capable de diagnostiquer l’instabilité de l’estimateur en absence de positivité pratique et présente une application sur les médicaments contre l’asthme durant la grossesse. Le deuxième manuscrit présente une procédure de sélection de modificateurs d’effet et d’estimation de l’effet conditionnel. En effet, cet article utilise une procédure de régularisation en deux étapes et peut être appliqué sur plusieurs logiciels standards. Finalement, il présente une application sur les médicaments contre l’asthme durant la grossesse. Le dernier manuscrit développe une méthodologie pour ajuster un biais de sélection dans une base de données administratives dans le but d’estimer une moyenne d’une population, et ce, en présence d’un échantillon probabiliste provenant de la même population avec des co-variables communes. En utilisant une méthode de régularisation, il montre qu’il est possible de sélectionner statistiquement les bonnes variables à ajuster dans le but de réduire l’erreur quadratique moyenne et la variance. Cet article décrit ensuite une application sur l’impact de la COVID-19 sur les Canadiens. / Randomized clinical trials (RCTs) are the gold standard for establishing causal effects and evaluating drug efficacy. However, RCTs are not always feasible and the usage of administrative data for the estimation of a causal parameter is an alternative solution. The main subject of this thesis can be divided into two parts, the whole comprised of three articles. The first part studies the usage of doubly robust estimators in causal inference using administrative data and machine learning. Examples of doubly robust estimators are Targeted Maximum Likelihood Estimation (TMLE; [73]) and Augmented Inverse Probability of Treatment Weighting (AIPTW; [51]). These methods are more and more present in pharmacoepidemiology [65, 102, 86, 7, 37]. In the second part of this thesis, we develop a doubly robust estimator and extend an existing one [121] for the setting of administrative data with a supplemental probability sample. The first paper of this thesis proposes a diagnostic tool that uses re-sampling methods to identify instability in doubly robust estimators when using data-adaptive methods in the presence of near practical positivity violations. It demonstrates the impact of machine learning methods for propensity score estimation when near practical positivity violations are induced. It then describes an analysis of asthma medication during pregnancy. The second manuscript develops a methodology to statistically select effect modifying variables using a two stage procedure in the context of a single time point exposure. It then describes an analysis of asthma medication during pregnancy. The third manuscript describes the development of a variable selection procedure using penalization for combining a nonprobability and probability sample in order to adjust for selection bias. It shows that we can statistically select the right subset of the variables when the true propensity score model is sparse. It demonstrates the benefit in terms of mean squared error and presents an application of the impact of COVID-19 on Canadians.

La majorité des femmes ayant été traitées pour un cancer du sein sont physiquement inactives alors que l’activité physique (AP) pourrait atténuer les conséquences néfastes du cancer et des traitements. Le soutien à l’autonomie par les professionnels de la santé peut améliorer l’adhésion et le maintien de l’AP. Or, peu d’études portent sur les populations en cancer et la plupart utilisent des devis qui limitent l’inférence causale. L’objectif du présent mémoire est de déterminer, à l’aide d’une approche en inférence causale, si la perception du soutien à l’autonomie (PSA) par des professionnels de la santé est associée à l’AP d’intensités légère, modérée et vigoureuse chez des femmes ayant été traitées pour un cancer du sein. Les données ont été collectées dans le cadre de l’étude longitudinale « Life After Breast Cancer : Moving On » (n=199). La PSA a été mesurée par le questionnaire Healthcare Climate Questionnaire. L’AP a été mesurée à l’aide d’accéléromètres triaxiaux GT3X. L’association entre la PSA et l’AP a été estimée à l’aide régressions linéaires et les estimations ajustées ont été obtenues par pondération par l’inverse de la probabilité de traitement (IPTW). Les résultats montrent l’absence d’associations entre la PSA et l’AP d’intensités légère (β^(95%IC) = -0,09 (-0,68 ; 0,49)), modérée (β^(95%IC) = -0,03 (-0,17 ; 0,11)) ou vigoureuse (β^(95%IC) = 0,00 (-0,03 ; 0,02)). D’autres formes de soutien à l’AP par les professionnels de la santé pourraient être envisagées pour encourager les femmes ayant été traitées pour un cancer du sein à adopter et maintenir une pratique régulière d’AP. / The majority of women that have been treated for breast cancer are physically inactive although physical activity (PA) could attenuate some of the adverse consequences of cancer and treatment. Autonomy support from health care professionals may improve PA adherence and maintenance. However, few studies on this topic focus on people treated for cancer and most use designs that limit causal inference. This master’s thesis aimed to determine, using a causal inference approach, whether or not perceived autonomy support (PAS) from health care professionals is associated with light, moderate, and vigorous intensity PA among women treated for breast cancer. Data were from the longitudinal study “Life After Breast Cancer: Moving On” (n=199). PAS was measured with the Healthcare Climate Questionnaire. PA was measured using the GT3X triaxial accelerometers. Associations between PAS and PA were estimated with linear regressions and adjusted estimations were obtained using propensity score-based inverse probability of treatment weights (IPTW). Results reveal no association between PAS and PA of light (β^(95%CI) = -0.09 (-0.68, 0.49)), moderate (β^(95%CI) = -0.03 (-0.17, 0.11)), or vigorous (β^(95%CI) = 0.00 (-0.03, 0.02)) intensity. Other forms of support for PA by health care professionals could be examined to encourage women to adopt and maintain regular PA.