Biostatistics for Epidemiology and Public Health Using ReBook - 2016
Chan presents a textbook for learning the open-source R statistics software with an emphasis on applications in epidemiology, public health and preventive medicine. He covers research and design in epidemiology and public health; data analysis using R programming; graphics using R; probability and statistics in biostatistics; case-control studies and cohort studies in epidemiology; and randomized trials, phase development, confounding in survival analysis, and logistic regressions. Students should have some background in basic computer use. Annotation ©2016 Ringgold, Inc., Portland, OR (protoview.com)
‚Äú[P]rovides a comprehensive explanation for data analysis and graphics using R language, including how R language handles classic problems in case-control, cohort studies and its use in survival analysis... The content and quality of this book is excellent. It is a great tool for understanding the use of R language for biostatistical analysis. Score: 91 - 4 Stars!‚Äù
‚ÄîBhavesh Barad, MD, East Tennessee State University Quillen College of Medicine, Doody's Reviews
Since it first appeared in 1996, the open-source programming language R has become increasingly popular as an environment for statistical analysis and graphical output. In addition to being freely available, R offers several advantages for biostatistics, including strong graphics capabilities, the ability to write customized functions, and its extensibility. This is the first textbook to present classical biostatistical analysis for epidemiology and related public health sciences to students using the R language. Based on the assumption that readers have minimal familiarity with statistical concepts, the author uses a step-bystep approach to building skills.
The text encompasses biostatistics from basic descriptive and quantitative statistics to survival analysis and missing data analysis in epidemiology. Illustrative examples, including real-life research problems and exercises drawn from such areas as nutrition, environmental health, and behavioral health, engage students and reinforce the understanding of R. These examples illustrate the replication of R for biostatistical calculations and graphical display of results. The text covers both essential and advanced techniques and applications in biostatistics that are relevant to epidemiology. This text is supplemented with teaching resources, including an online guide for students in solving exercises and an instructor's manual.
- First overview biostatistics textbook for epidemiology and public health that uses the open-source R program
- Covers essential and advanced techniques and applications in biostatistics as relevant to epidemiology
- Features abundant examples and exercises to illustrate the application of R language for biostatistical calculations and graphical displays of results
- Includes online student solutions guide and instructor's manual