This two-day intensive workshop will go over opportunities and potentials of EMR/EHR for health and medical studies, statistical challenges, and pitfalls for analyzing EMR/EHR, and the latest developments of multiple techniques to address those challenges, followed by hands-on computer lab sessions and case studies to put concepts into practice.
By the end of the electronic medical records training, participants will be familiar with the following topics:
- Power and potentials of EMR/EHR data
- Open-access datasets across the world
- Preparation, transformation, and integration of EMR/EHR
- Confounding, bias, and missing data in EMR/EHR and statistical methods addressing these challenges
- Statistical methods for comparative effectiveness
- Statistical methods for predictive analysis
Investigators at all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate. Please note this training is live-stream, virtual training. It is not a self-paced, online course.
PREREQUISITES AND REQUIREMENTS
- Each participant must have an introductory background in statistics.
- Each participant must be familiar with R.
- Each participant must have a laptop with R and RStudio downloaded and installed prior to the first day of the training.
INSTRUCTORS
- Shuang Wang, PhD, Department of Biostatistics, Columbia University
- Ying Wei, PhD, Department of Biostatistics, Columbia University
ADDITIONAL INFORMATION
- Scholarships are available: https://www.publichealth.columbia.edu/research/precision-prevention/professional-development-scholarships
- Subscribe for updates: http://eepurl.com/gNkfHf
- Email our team: [email protected]
Capacity is limited. Paid Registration is required to attend.