Events

Provided by the TRaining And Nurturing Scholars FOr Research that is Multidisciplinary TRANSFORM Resource Reach for the First R01 Workshop The Reach for the First R01 Workshop is available twice a year to promising junior faculty. Up to six junior investigators are selected for this workshop each term (fall and spring), across all departments.  Successful applicants will receive:  Five free hours of biostatistical consulting  Access to other Irving Institute services and programs  Two expert pre-reviews on an early draft of their R01 application  Bimonthly, closely monitored meetings to ensure structure and timeliness in completing the tasks required to successfully submit a first R01 application. These resources are intended to enhance, rather than replace, appropriate mentoring. An applicant without excellent mentoring cannot be seen as competitive for this workshop.    The Reach for the R01 Workshop is led by Drs. R.T. Ogden and Mary Beth Terry 2022 Course Sessions (In-Person Friday afternoons, 3:00pm - 4:30pm)   September 23rd – Intro. Session   October 7th – Aims   October 21st – Significance/Innovation   November 11th – Budget Justification/Biosketch    December 2nd – Approach   December 16th – Mock Study Session Application Deadline: Wednesday, August 31st, 2022

In the Web Content Strategy Training, we review best practices for content creation, SEO, and web accessibility. The goal of the class is to review web-writing guidelines before you create content and to learn how to best present your content for your intended audience.

Environmental Justice Boot Camp: Theory and Methods to Study Environmental Health Disparities The Environmental Justice Boot Camp is a two-day intensive course featuring seminars and applied analytical sessions on key concepts, exposure assessment techniques, epidemiologic methods, community engagement and health policy applications, and statistical analytic approaches for conducting effective and solution-driven environmental justice research. This two-day boot camp will provide environmental health scientists with training in environmental justice research. The boot camp’s multi-disciplinary approach will cover the steps involved in conducting informed, effective, and solution-driven environmental justice and health disparities research. Our team consists of scientists with over 30 years of combined research in the fields of environmental health, sociology, epidemiology, health policy, community engagement, and biostatistics. Lectures will cover key concepts, frameworks, and methods for conducting environmental justice research. We will then build on this knowledge with hands-on learning experiences from case studies that allow participants to apply real-world datasets to address key research questions in environmental health and health disparities using exposure assessment techniques, epidemiologic methods, and analytic approaches, such as interaction and mediation.   By the end of the workshop, participants will be familiar with the following topics:  Key concepts of environmental justice and health disparities  Epidemiologic conceptual framework  Study design advantages and challenges  Data collection, questionnaire design, and measurement error  Data analysis: basics of interaction and mediation  Emerging topics and methods in environmental justice research  Investigators at all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate.  PREREQUISITES AND REQUIREMENTS There are two prerequisites and requirements to attend this training:  Basic familiarity with R is recommended to get the most out of the Boot Camp. If you have not used this platform before or need a refresher, step through the tutorials outlined below so you have the basic skills needed for Boot Camp success.  Each participant is required to have a personal laptop/computer and a free, basic RStudio Cloud account. All lab sessions will be done using RStudio Cloud. ADDITIONAL INFORMATION Register or view more information. Subscribe for updates. Email us at ColumbiaSHARP.EJ@gmail.com. Capacity is limited. Paid registration is required to attend.

Causal Mediation Analysis Training: Methods and Applications Using Health Data The Causal Mediation Analysis Training is a 3-day intensive boot camp of seminars and hands-on analytical sessions to provide an overview of concepts and data analysis methods used to investigate mediating mechanisms. This three-day intensive course will cover some of the recent developments in causal mediation analysis and provide practical tools to implement these techniques and assess the mechanisms and pathways by which causal effects operate. Led by a team of experts in causal mediation techniques at Columbia University, this course will integrate lectures and discussion with hands-on computer lab sessions using R. The course will cover the relationship between traditional methods for mediation in environmental health, epidemiology, and the social sciences and new methods in causal inference using a wide variety of examples to illustrate the techniques and approaches. We will discuss 1) when the standard approaches to mediation analysis are valid for dichotomous, and continuous, outcomes, 2) alternative mediation analysis techniques when the standard approaches will not work, using ideas from causal inference and natural direct and indirect effects 3) the no-unmeasured confounding assumptions needed to identify these effects, and 4) how regression approaches for mediation analysis can be extended in the presence of multiple mediators.  By the end of the workshop, participants will be able to:  Understand when traditional methods for mediation fail  Articulate concepts about mediation under the counterfactual framework and assumptions for identification  Formulate and apply regression approaches for mediation for single and multiple mediators  Develop facility with the use of software for mediation and interpretation of software output  Investigators at all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate.  PREREQUISITES AND REQUIREMENTS Each participant must be familiar with linear and logistic regression.  Each participant must have experience with programming in R.   Although the instructors will provide an overview of the fundamentals of causal inference (potential outcomes, directed acyclic graphs, and marginal structural models), we invite the participants to read chapters 1-7, 11, and 12 of Hernán MA, Robins JM (2020). Causal Inference: What If. Boca Raton: Chapman & Hall/CRC (free). Each participant is required to have a personal computer and a free, basic RStudio Cloud account. All lab sessions will be done using RStudio Cloud.  ADDITIONAL INFORMATION Register or view more information. Subscribe for updates. Email us at Columbia.CMA@gmail.com. Capacity is limited. Paid registration is required to attend.