2023 SORA-TABA Annual Workshop & DLSPH Biostatistics Research Day

Dalla Lana School of Public Health, Biostatistics, University of Toronto

Dalla Lana School of Public Health

The Division of Biostatistics in the Dalla Lana School of Public Health at the University of Toronto is pleased to host the SORA-TABA Annual Workshop &amp; DLSPH Biostatistics Research Day. The event brings together regional and local statistical communities who are interested in biostatistics, artificial intelligence, data science, financial statistics, and other applied areas of statistics. Please join us in making this event a great success!In addition to the workshop, the event will showcase student research posters. Students and post-docs are encouraged to present their research or practicum work, and three Paul Corey Memorial Student Poster Presentation Award will be awarded.Please provide poster abstracts for review on or before Friday, April 28th at 5pm via the online <a href="https://forms.office.com/Pages/ResponsePage.aspx?id=JsKqeAMvTUuQN7RtVsVSENty8hLvHV5Nm72wzWNeerRUQVZZWTlQSFc1TFk3SUVTUkIyNzI4VklFMy4u" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Abstract Submissions</a> form. Information for prospective poster presenters, including submission timelines, poster dimensions and the assessment rubric is provided within the abstract submission form. Poster presenters are not required to register for the workshop but must be available in-person during the poster presentation period. If you have any questions, please email Ryan Rosner at biostat.dlsph@utoronto.ca. <h2>Fundamentals of Causal Inference: With R</h2>Instructor: Professor Emerita Babette Brumback; University of Florida, Department of BiostatisticsAbstract: One of the primary motivations for clinical trials and observational studies of humans is to infer cause and effect. Disentangling causation from confounding is of utmost importance. Fundamentals of Causal Inference: With R explains and relates different methods of confounding adjustment in terms of potential outcomes and graphical models, including standardization, doubly robust estimation, difference-in-differences estimation, front-door estimation, and instrumental variables estimation. These methods are compared in terms of estimating the average effect of treatment on the treated (ATT). The fundamentals of mediation analysis and adjusting for time-dependent confounding are also presented. Several real data examples, simulation studies, and analyses using R motivate and illustrate the methods throughout. The course assumes familiarity with basic statistics and probability, regression, and R. The course will be taught with a blend of lecture and worked examples.Program:M﻿odule 1 (1.5hrs): Introduction ﻿ a) Definitions and Datasets ﻿ b)Potential Outcomes Framework ﻿ c)Directed Acyclic GraphsM﻿odule 2 (1.5hrs): Adjusting for Confounding Part One ﻿ a) Standardization ﻿ b) Difference-in-Differences EstimationM﻿odule 3 (1.5hrs): Adjusting for Confounding Part Two ﻿ a) Front-Door Estimation ﻿ b) Instrumental Variables Estimation c) Comparison of the Four Methods (in terms of estimating the average effect of treatment on the treated, or ATT)M﻿odule 4 (1.5hrs): More Advanced Topics ﻿ a) Mediation ﻿ b) Time-Dependent Confounding (time permitting)Speaker Bio: Babette Brumback is known for her work on causal inference. She is the author of the recently published textbook, Fundamentals of Causal Inference: With R. Babette is Professor Emerita of Biostatistics at the University of Florida, and she is an elected member of Delta Omega and a Fellow of the American Statistical Association. Babette’s statistical research has concentrated on methods for longitudinal data analysis, causal modeling, bias adjustment, and analysis of data from complex sampling designs. She has also collaborated extensively on public health and medical studies concerning a broad array of research areas.Agenda<ul><li>08:15-9:00 Registration &amp; Breakfast</li><li>0﻿9:00-09:15 Opening Remarks</li><li>09:15-10:45 Module 1</li><li>10:45-11:00 Morning Break</li><li>11:00-12:30 Module 2</li><li>12:30-13:30 Lunch/Poster presentation assessment</li><li>13:30-15:00 Module 3</li><li>15:00-15:15 Afternoon Break </li><li>15:15-16:45 Module 4</li><li>16:45-17:00 Closing Remarks</li></ul>***Registrants will be provided access to recordings of the workshop for three weeks following the event***Questions can be directed to Ryan Rosner at biostat.dlsph@utoronto.caNo refunds will be provided

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