1st Edition
Longitudinal Analysis of Real World Time-to-event Data in Health Care Big Data Approach using R
By Atanu Bhattacharjee
Copyright 2026
236 Pages
23 B/W Illustrations
by
Chapman & Hall
236 Pages
23 B/W Illustrations
by
Chapman & Hall
Also available as eBook on:
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... Read more
1. Big Data, Real-World Evidence, and R. 2. Preparing and Exploring Real-World Longitudinal Data in R. 3. Survival Analysis in Real World Evidence Data. 4. Longitudinal Data Analysis in Real-World Evidence. 5. Longitudinal Analysis in Real World Evidence Data. 6. Landmark Data Analysis in Real-World Evidence. 7. Joint Longitudinal and Survival Analysis in Real-World Evidence. 8. Prediction Models with Longitudinal Data. 9. Bayesian Analysis of Big Longitudinal Data.
Biography
Atanu Bhattacharjee is a medical statistician the University of Leicester. He is an expert in the field of medical statistics, with a focus on survival analysis, competing risks, and high-dimensional data. Bhattacharjee’s research interests include the development of new statistical methods for the analysis of time-to-event data, with a focus on the analysis of competing risks and high-dimensional data. He has published several research papers and articles in leading statistical journals on these topics. Bhattacharjee has also contributed to the development of R package, which can be used to perform competing risks analysis and high-dimensional data analysis respectively.
