Workshop: Forest plots in practical use – implementation and interpretation
Forest plots are essential for visualizing model outputs in pharmacometric analysis. This workshop provides hands-on training in creating and interpreting Forest plots using R, NONMEM, and PsN.
Overview
This workshop delivers a comprehensive approach to Forest plots, from interpretation to implementation. Participants will explore key statistical assumptions, learn best practices for creating plots in R, and understand how modeling methodology impacts inference. Hands-on exercises will reinforce learning through real-world case studies.
Workshop goals
To equip the participants with a solid foundation in Forest plot analysis for pharmacometric modeling.
Workshop learning objectives
By the end of this workshop, participants will:
- Interpret Forest plots considering variations in point estimates, uncertainties, and reference conditions.
- Create Forest plots using model output from NONMEM, PsN, and R.
- Understand how modeling methodologies impact inference and how “Full Model-like inference” can be achieved from modeling approaches that generate parsimonious covariate models.
Key topics covered
- Fundamentals of Forest plot interpretation
- Techniques for analyzing point estimates and uncertainty
- Reference conditions in modeling
- Hands-on Forest plot creation using R, NONMEM, and PsN
- Covariate modeling techniques for enhanced analysis
- Impact of modeling methodologies on inference accuracy
Target audience
This workshop is ideal for scientists and pharmacometricians seeking deeper expertise in Forest plot analysis. It is suitable for students, early-career professionals, and experienced users refining their skills.
Workshop requirements
Participants must bring a laptop with the required software installed (R, NONMEM, and PsN).
Basic knowledge of pharmacometrics and data visualization is recommended but not required.
Ready to discuss your workshop needs?
Email us at communication@pharmetheus.com