Longitudinal Analysis of Real World Data by Atanu Bhattacharjee(.PDF)+
File Size: 24.9 MB
Longitudinal Analysis of Real World Time-to-event Data in Health Care: Big Data Approach using R by Atanu Bhattacharjee
Requirements: .ePUB, .PDF reader, 24.9 MB | True PDF, True EPUB
Overview: 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. It covers data preprocessing, integration, and advanced modelling techniques to serve as a valuable resource for professionals and researchers seeking evidence-based decision-making in healthcare and related fields. R has emerged as a powerful tool for data analysis, visualization, and modeling across various disciplines. It offers a comprehensive suite of statistical and graphical techniques, including linear and nonlinear modeling, time series analysis, classification, and clustering. R’s open-source nature and extensive package ecosystem make it highly versatile and adaptable to new methodologies. Researchers have utilized R for diverse applications, such as big data analytics, road traffic accident analysis, and growth curve modeling. Its data visualization capabilities are particularly noteworthy, enabling effective trend detection and variable correlation analysis. R’s strengths in data manipulation, calculation, and graphical display make it especially valuable in social sciences. As a result, R has become the lingua franca of statistics and continues to grow in popularity among statisticians and data scientists.
Genre: Non-Fiction > Tech & Devices
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