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 principle 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.
Investigators from all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate.
Additional Information:
There are three requirements to attend this training:
1. Each participant must be familiar with common methods of statistical analysis of complete data, such as multiple regression and logistic regression.
2. Each participant must have experience with programming in R.
3. 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.
Visit training website for more information: https://www.publichealth.columbia.edu/academics/non-degree-special-programs/professional-non-degree-programs/skills-health-research-professionals-sharp-training/statistical-analysis-missing-data
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Contact the Boot Camp Team: Columbia.StatisticalAnalysis@gmail.com
Capacity is limited. Paid registration is required to attend.
