37 research outputs found

    Minimum Wages and Racial Inequities in Cardiovascular Disease: Rethinking Difference-in-Differences

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    Large U.S. Black-White inequities in cardiovascular disease (CVD) morbidity and mortality havepersisted for nearly a century, and are believed to arise in part from socioeconomic inequalitystructurally linked to racism. Research comparing the effects of realistic policy proposals on CVDinequities would be useful to inform societal action aimed at eliminating these, but such research hasbeen nearly nonexistent to date. This effort has been hindered by a lack of rigorous policy evaluationmethods meant to help us learn about hypothetical new policies. In this dissertation, I characterize a new study design called staggered discontinuation design(SDD), develop an identification and estimation approach under this design, and apply this approach tothe effect of a hypothetical federal minimum wage increase on CVD mortality for Black and Whitepeople in the U.S. SDD extends difference-in-differences (DID) by using variation in the timing ofdiscontinuation from a time-varying treatment regime to identify effects of that regime under the“parallel trends” assumption commonly employed in DID. Natural estimators for these effects arise fromexisting estimators of Robins’s (1986) g-computation algorithm formula, including iterated conditionalexpectation (ICE) g-computation, inverse-probability of treatment weighted (IPTW) marginal structuralmodels, and targeted maximum likelihood. To address the substantive question, I use data fromREGARDS, a large, approximately nationally representative cohort study with over 15 years of follow-upfor adjudicated CVD outcomes, along with publically available state-level policy data. I estimate the effects of a gradual federal minimum increase to $11.10/hour on the race-specific risk functions forBlack and White people in the U.S. using an inverse-probability-weighted estimator. Analytic proof and simulation support the supposition that the proposed estimators areconsistent and asymptotically normally distributed under the stated assumptions. If causal and modelingassumptions hold, estimates suggest the effect of the hypothetical policy would have been tomoderately decrease risk of CVD mortality across the study period for both Black and white people, withthe effect somewhat greater for Black people, leading to a moderately decreased absolute disparity at10 years. However, inference is very imprecise relative to the magnitude of these estimates, leading toconfidence intervals that include large increases and decreases in risk for both groups and in theabsolute disparity measure. Additional research using larger data sources and/or alternative methods isneeded to inform minimum wage policy with public health in mind.Doctor of Philosoph

    Le dĂ©bat de sociĂ©tĂ© public rĂ©gulĂ© en anglais langue Ă©trangĂšre en Belgique francophone. État des lieux sur les pratiques dĂ©clarĂ©es et expĂ©rimentation d’un enseignement explicite vs implicite du genre

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    Force est de constater que les genres textuels suscitent depuis plusieurs dĂ©cennies un vif intĂ©rĂȘt dans les champs d’études linguistiques, mais Ă©galement didactiques. Ainsi, une vaste littĂ©rature scientifique internationale (notamment suisse, canadienne, brĂ©silienne, australienne) sur l’étude des genres textuels s’est progressivement dĂ©veloppĂ©e. Toutefois, ce domaine de recherche semble susciter relativement peu d’intĂ©rĂȘt en Belgique francophone. À l’instar de plusieurs chercheur·es (Lousada, 2008 ; GuimarĂŁes-Santos, 2018 ; Simons, 2018), nous estimons que le genre textuel est assurĂ©ment un aspect important de l’approche communicative, mais qu’il l’est sans doute encore davantage dans la perspective actionnelle prĂ©conisĂ©e par les auteur·es du Cadre europĂ©en commun de rĂ©fĂ©rence pour les langues (Conseil de l’Europe, 2001), lequel influence considĂ©rablement les politiques Ă©ducatives en Europe. En effet, il nous semble que le recours Ă  l’étude du genre textuel donne non seulement du sens Ă  l’apprentissage, mais qu’il permet Ă©galement Ă  l’élĂšve de mieux comprendre la sociĂ©tĂ© dans laquelle il·elle Ă©volue(ra) et surtout de s’y insĂ©rer et d’y intervenir en tant qu’acteur·rice social·e, ce qui est l’un des objectifs prioritaires de la perspective actionnelle (Bento, 2013 ; Puren, 2006, 2014 ; Rosen, 2009) . Parmi les genres textuels, il nous a semblĂ©Ì particuliĂšrement important d’étudier le dĂ©bat de sociĂ©tĂ© public rĂ©gulĂ©. En effet, il vĂ©hicule, entre autres, des valeurs dĂ©mocratiques (Ă©coute, respect, tolĂ©rance) et permet l’acquisition de nombreuses compĂ©tences linguistiques (lexique, grammaire, fonctions langagiĂšres...), gĂ©nĂ©riques (tour de parole, tĂąche du·de la modĂ©rateur·rice, structure du dĂ©bat...) et de vie (savoir prendre des dĂ©cisions, savoir gĂ©rer ses Ă©motions, dĂ©velopper une pensĂ©e critique...). De plus, le dĂ©bat de sociĂ©tĂ© public rĂ©gulĂ© permet d’exercer, en classe de langues Ă©trangĂšres, les compĂ©tences d’interaction orale et d’audition, mais il permet aussi de travailler les compĂ©tences de lecture et d’écriture. De nombreuses stratĂ©gies de communication (pallier un manque linguistique, faire rĂ©pĂ©ter, interrompre, demander de parler moins vite...) peuvent Ă©galement ĂȘtre mises en pratique Ă  travers celui-ci. Enfin, si le monde anglo-saxon normalise, depuis de trĂšs nombreuses annĂ©es, l’enseignement du dĂ©bat grĂące Ă  de nombreux clubs au sein des institutions scolaires, aux sessions de cours axĂ©es sur cette thĂ©matique et aux diverses compĂ©titions qui se dĂ©roulent rĂ©guliĂšrement en Grande-Bretagne et aux États-Unis notamment, le monde francophone, en revanche, semble beaucoup plus frileux quant Ă  son enseignement. L’enseignement du dĂ©bat de sociĂ©tĂ© public rĂ©gulĂ© reprĂ©sentait donc un objet d’étude inĂ©dit Ă  explorer en Belgique francophone. Nous avons Ă©tudiĂ© le dĂ©bat de sociĂ©tĂ© public rĂ©gulĂ© selon deux approches : explicite et implicite. On peut, en effet, penser que certain·es enseignant·es exposent leurs Ă©lĂšves Ă  diffĂ©rentes formes de DSPR, mais n’explicitent pas sa structure interne, ni mĂȘme les savoirs et savoir-faire linguistiques, ni les attitudes que le dĂ©bat mobilise. Dans ce cas, l’apprentissage se fait de maniĂšre implicite, notamment par exposition Ă  diffĂ©rents inputs, par imprĂ©gnation, puis par imitation. En revanche, les tenant·es d’un enseignement explicite (notamment ClĂ©ment, 2015 ; Gauthier et al., 2013 et Rosenshine, 1986) estiment qu’il importe d’aider les Ă©lĂšves Ă  identifier les savoirs en jeu et d’expliciter ces derniers avant de les exercer sĂ©parĂ©ment, puis de les mobiliser dans une « tĂąche complexe ». Relevons au passage que cette variable explicite vs implicite est en lien direct avec la notion d’équitĂ©, qui est au cƓur des dĂ©bats actuels sur l’enseignement

    Enseigner le débat en classe de LE

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    PPT présenté aux étudiants de master à finalité didactique LE lors du module sur les genres textuels. Présentation en 3 parties sur l'enseignement du débat en classe de LE: 1) Le débat de société public régulé 2) L'enseignement explicite 3) Exemple de séquence didactique par la situation problÚme

    Faire entrer le dĂ©bat en classe d’anglais L2 : des processus d’analyse des pratiques sociales de rĂ©fĂ©rence aux processus IN Symposium : Le texte (et le genre de texte), levier didactique pour un retour du sujet et du sens dans l’enseignement des langues en contextes plurilingues ?de transposition didactique

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    peer reviewedCommunication prĂ©sentĂ©e lors du symposium : Le texte (et le genre de texte), levier didactique pour un retour du sujet et du sens dans l’enseignement des langues en contextes plurilingues ? coordonnĂ© par Eliane Lousada (UniversitĂ© de SĂŁo Paulo) et Sandrine Aeby DaghĂ© (UniversitĂ© de GenĂšve)

    Transporting treatment effects from difference-in-differences studies

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    Difference-in-differences (DID) is a popular approach to identify the causal effects of treatments and policies in the presence of unmeasured confounding. DID identifies the sample average treatment effect in the treated (SATT). However, a goal of such research is often to inform decision-making in target populations outside the treated sample. Transportability methods have been developed to extend inferences from study samples to external target populations; these methods have primarily been developed and applied in settings where identification is based on conditional independence between the treatment and potential outcomes, such as in a randomized trial. This paper develops identification and estimators for effects in a target population, based on DID conducted in a study sample that differs from the target population. We present a range of assumptions under which one may identify causal effects in the target population and employ causal diagrams to illustrate these assumptions. In most realistic settings, results depend critically on the assumption that any unmeasured confounders are not effect measure modifiers on the scale of the effect of interest. We develop several estimators of transported effects, including a doubly robust estimator based on the efficient influence function. Simulation results support theoretical properties of the proposed estimators. We discuss the potential application of our approach to a study of the effects of a US federal smoke-free housing policy, where the original study was conducted in New York City alone and the goal is extend inferences to other US cities

    Identifying and estimating effects of sustained interventions under parallel trends assumptions

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    Many research questions in public health and medicine concern sustained interventions in populations defined by substantive priorities. Existing methods to answer such questions typically require a measured covariate set sufficient to control confounding, which can be questionable in observational studies. Differences-in-differences relies instead on the parallel trends assumption, allowing for some types of time-invariant unmeasured confounding. However, most existing difference-in-differences implementations are limited to point treatments in restricted subpopulations. We derive identification results for population effects of sustained treatments under parallel trends assumptions. In particular, in settings where all individuals begin follow-up with exposure status consistent with the treatment plan of interest but may deviate at later times, a version of Robins' g-formula identifies the intervention-specific mean under SUTVA, positivity, and parallel trends. We develop consistent asymptotically normal estimators based on inverse-probability weighting, outcome regression, and a double robust estimator based on targeted maximum likelihood. Simulation studies confirm theoretical results and support the use of the proposed estimators at realistic sample sizes. As an example, the methods are used to estimate the effect of a hypothetical federal stay-at-home order on all-cause mortality during the COVID-19 pandemic in spring 2020 in the United States.Comment: 15 pages, 2 figure

    Strengthening The Organization and Reporting of Microbiome Studies (STORMS): A Reporting Checklist for Human Microbiome Research

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    Background Human microbiome research is a growing field with the potential for improving our understanding and treatment of diseases and other conditions. The field is interdisciplinary, making concise organization and reporting of results across different styles of epidemiology, biology, bioinformatics, translational medicine, and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Methods A multidisciplinary group of microbiome epidemiology researchers reviewed elements of available reporting guidelines for observational and genetic studies and adapted these for application to culture-independent human microbiome studies. New reporting elements were developed for laboratory, bioinformatic, and statistical analyses tailored to microbiome studies, and other parts of these checklists were streamlined to keep reporting manageable. Results STORMS is a 17-item checklist for reporting on human microbiome studies, organized into six sections covering typical sections of a scientific publication, presented as a table with space for author-provided details and intended for inclusion in supplementary materials. Conclusions STORMS provides guidance for authors and standardization for interdisciplinary microbiome studies, facilitating complete and concise reporting and augments information extraction for downstream applications. Availability The STORMS checklist is available as a versioned spreadsheet from https://www.stormsmicrobiome.org/
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