Senior Systems Engineer, JMP
Rob Lievense is a Senior Systems Engineer at JMP. He works with federal government customers showing them how to utilize JMP to extract useful information from data. He is also an active professor of statistics at Grand Valley State University (GVSU), located in Allendale, Michigan. Prior to joining JMP, Rob was a Research Fellow of Global Statistics at Perrigo where he led a group that supported the consumer health care research and development department with statistical analysis, data visualization, advanced modeling, date-driven Quality by Design for product development, and structured experimental design planning. Rob has more than 20 years of experience in the applied statistics industry and 10 years of experience in the use of JMP. He has presented at major conferences including JMP Discovery Summit, where he served on the Steering Committee, and the annual conference of the American Association of Pharmaceutical Scientists. Rob has a BS in Applied Statistics and an MS in Biostatistics from GVSU. He currently serves as Member of the Biostatistics Curriculum Development Committee for GVSU and has his Six Sigma Black Belt Certification.
By This Author
Pharmaceutical Quality by Design Using JMP®: Solving Product Development and Manufacturing Problems
by Rob Lievense
Pharmaceutical Quality by Design Using JMP®: Solving Product Development and Manufacturing Problems provides broad-based techniques available in JMP to visualize data and run statistical analyses for areas common in healthcare product manufacturing.
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- Douglas E. Faries is Senior Research Advisor at Lilly USA, where he oversees statistical design and analysis support for Health Outcomes Research.
- Felicitas Kuehne is a Senior Scientist in Health Decision Science and Epidemiology and Coordinator of the Program on Causal Inference in Science at the Department of Public Health, Health Services Research and Health Technology Assessment at UMIT in Austria. She conducts decision-analytic modeling studies for causal research questions in several disease areas and teaches epidemiology and causal inference. She is the Coordinator of the HTADS course “Causal Inference in Observational Studies and Clinical Trials Affected by Treatment Switching: A Practical Hands-on Workshop.”
- Prof. Uwe Siebert, MD, MPH, MSc, ScD is a Professor of Public Health, Medical Decision Making and Health Technology Assessment, and Chair of the Department of Public Health, Health Services Research and HTA at UMIT – University for Health Sciences, Medical Informatics and Technology in Austria. He is also Adjunct Professor of Health Policy and Management at the Harvard Chan School of Public Health.