This book is aimed to compile typical fundamental to advanced
statistical methods to be used for health data sciences. This book
promotes the applications to health and health-related data.
However, the models in this book can be used to analyse any kind of
data. The data are analysed with the commonly used statistical
software of R/SAS (with online supplementary on SPSS/Stata). The
data and computing programs will be available to facilitate
readers' learning experience. There has been considerable attention
to making statistical methods and analytics available to health
data science researchers and students. This book brings it all
together to provide a concise point-of-reference for most commonly
used statistical methods from the fundamental level to the advanced
level. We envisage this book will contribute to the rapid
development in health data science. We provide straightforward
explanations of the collected statistical theory and models,
compilations of a variety of publicly available data, and
illustrations of data analytics using commonly used statistical
software of SAS/R. We will have the data and computer programs
available for readers to replicate and implement the new methods.
The primary readers would be applied data scientists and
practitioners in any field of data science, applied statistical
analysts and scientists in public health, academic researchers, and
graduate students in statistics and biostatistics. The secondary
readers would be R&D professionals/practitioners in industry
and governmental agencies. This book can be used for both teaching
and applied research.
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