Events

The Statistical Analysis with Missing Data Workshop is a two-day intensive workshop of seminars and hands-on analytical sessions to provide an overview of concepts, methods, and applications for statistical analysis of health studies with missing data. This two-day intensive workshop integrates the principal concepts and methods commonly used in statistical analysis with missing data and their applications in surveys, longitudinal studies, and clinical trials. Led by a team of renowned experts in missing data research, this workshop will integrate seminar lectures with hands-on computer lab sessions and case studies to put concepts into practice. We will cover weighting, maximum likelihood, Bayes, and multiple imputation methods and use a wide variety of examples to illustrate the techniques and approaches. We will also discuss methods for missing not at random and the latest developments on missing data research. By the end of the workshop, participants will be familiar with the following topics: Missing data patterns and mechanisms Weighting methods Maximum likelihood methods Bayes and multiple imputation Approaches to missing not at random Missing data in surveys Missing data in longitudinal studies Missing data in clinical trials Audience and Requirements Investigators from all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate. There are three requirements to attend this training: Each participant must be familiar with common methods of statistical analysis of complete data, such as multiple regression and logistic regression. Each participant must have experience with programming in R. Each participant is required to bring a personal laptop as all lab sessions will be done on your personal laptop. Each participant must have R downloaded and installed prior to attending the Workshop. Instructors Roderick J. Little, PhD, University of Michigan School of Public Health. Roderick J. Little is Richard D.  Qixuan Chen, PhD, Mailman School of Public Health, Columbia University. Qixuan Chen is Associate Professor of Biostatistics at Columbia University. Additional Information Subscribe for updates on new Training details and registration deadlines. Contact the Boot Camp team. Capacity is limited. Paid registration is required to attend.

Speaker: Saar Gill, MD, PhD, Associate Professor of Medicine in the Division of Hematology-Oncology, University of Pennsylvania, Perelman School of Medicine Hosted by Stavroula Kousteni, PhD, Professor, Department of Physiology & Cellular Biophysics; Director, Evans MDS Center at Columbia. This event is sponsored by the Herbert Irving Comprehensive Cancer Center's (HICCC) Edward P. Evans Center for Myelodysplastic Syndromes (MDS) at Columbia University, established to foster an all-encompassing approach in studying MDS giving us molecular, cellular genetic and epigenetic insights to develop and test innovative therapies.

Open Office hours is an open discussion and training session available to anyone who works on CUIMC websites. During this session you’ll be able to ask questions, go over real examples and get one-on-one training and support from CUIMC Web Services.

The Data Visualization and Presentation Essentials Workshopis a three-day intensive hands-on workshop designed for people and teams who want to develop their creative process to create better, more effective data visualizations and presentations. This three-day training combines two complementary skills that are essential for effective communication: data visualization and presentations. The first two days focus on data visualization and introduced attendees to the data design process. On the third day, participants shift to presentation skills, where they will learn practical strategies to design and deliver impactful presentations that communicate data and analysis with clarity. Data visualization—the study of visually representing data—plays a crucial role in the work of researchers, scientists, analysts, and communication professionals. Yet visualization is often an afterthought, secondary to analysis, limiting how effectively insights are shared. In the first part of this workshop, attendees learn how to conceptualize, plan, and develop visualizations using only basic drawing tools and office supplies. Through collaborative exercises, participants explore methods, styles, and best practices for creating meaningful and beautiful visualizations that enhance understanding and engagement. On day three, the focus shifts to presenting information. Even well-designed content can fall flat if the presentation is poorly structured or delivered. In this part of the workshop, attendees are introduced to a practical framework for planning, building, and giving better presentations. The course emphasizes slide design, message clarity, visual communication, and strategies for delivering more confident, persuasive talks. By the end of the workshop, participants will be familiar with the following topics: Learn how to increase message clarity and impact Identify different types, purposes, and structures of data visualizations Apply visualization best practices to increase clarity and impact Understand and apply the data visualization design process Begin developing their own visualization style Create more effective and compelling slide decks Improve how they communicate quantitative results and analysis Think critically about visual and narrative presentation choices Deliver presentations with improved confidence and effectiveness Audience and Requirements View Requirements for this training Additional Information Subscribe for updates on new training details and registration deadlines. Contact the Workshop team. Capacity is limited. Paid registration is required to attend.