Longitudinal Analysis of Real World Time-to-event Data in Health Care: Big Data Approach using R

This book presents a practical approach for researchers seeking to analyse patient data over time.It serves as a comprehensive guide, utilising the R programming language to analyse complex datasets efficiently.It provides step-by-step instructions and examples, aiding in data organisation and insightful analysis to accurately predict event occurrences and the impact of different variables on patient outcomes, enhancing decision-making in medical practice. • With practical examples and case studies, it helps to learn how to apply analysis techniques to real-world healthcare datasets, gaining insights into complex data for informed decision-making. • Offers comprehensive coverage of relevant techniques and methodologies, including essential topics such as Big Data characteristics, Real-World Evidence significance, real-world data sources, longitudinal and survival data analysis, prediction models, and Bayesian analysis, • R code examples enable readers to follow along and replicate anal