Clinical Data Validation

Mastering Data Management: Explore EDC Systems, Regulatory Compliance, Data Quality, and Emerging Technologies in Clinic

Navigate the complexities of clinical trials with expertise in GCP, ethical practices, and compliance.

Unlock the Mysteries of Clinical Trials and Medical Research – No Experience Needed!

Learn R Programming Language for Data Science, Machine Learning, Data Analysis and Data Visualization with Libraries

Elevate Your Laboratory Expertise: GLCP Mastery Course Certification and Beyond

This book provides insight and practical illustrations on how modern statistical concepts and regression methods can be applied in medical prediction problems, including diagnostic and prognostic outcomes. Many advances have been made in statistical approaches towards outcome prediction, but these innovations are insufficiently applied in medical research. Old-fashioned, data hungry methods are often used in data sets of limited size, validation of predictions is not done or done simplistically, and updating of previously developed models is not considered. A sensible strategy is needed for model development, validation, and updating, such that prediction models can better support medical practice.

The second edition of this volume provides insight and practical illustrations on how modern statistical concepts and regression methods can be applied in medical prediction problems, including diagnostic and prognostic outcomes. Many advances have been made in statistical approaches towards outcome prediction, but a sensible strategy is needed for model development, validation, and updating, such that prediction models can better support medical practice.