Innovative Statistical Methods for Public Health Data

Beschreibung

The book brings together experts working in public health and multi-disciplinary areas to present recent issues in statistical methodological development and their applications. This timely book will impact model development and data analyses of public health research across a wide spectrum of analysis. Data and software used in the studies are available for the reader to replicate the models and outcomes. The fifteen chapters range in focus from techniques for dealing with missing data with Bayesian estimation, health surveillance and population definition and implications in applied latent class analysis, to multiple comparison and meta-analysis in public health data. Researchers in biomedical and public health research will find this book to be a useful reference, and it can be used in graduate level classes.
The book brings together experts working in public health and multi-disciplinary areas to present recent issues in statistical methodological development and their applications. This timely book will impact model development and data analyses of public health research across a wide spectrum of analysis. Data and software used in the studies are available for the reader to replicate the models and outcomes. The fifteen chapters range in focus from techniques for dealing with missing data with Bayesian estimation, health surveillance and population definition and implications in applied latent class analysis, to multiple comparison and meta-analysis in public health data. Researchers in biomedical and public health research will find this book to be a useful reference and it can be used in graduate level classes.
Covers statistical methods and their applications to public health research in a multi-disciplinary approach by experts in the field Compiles the data & related software in innovative statistical methods so readers can use the software for their own data analysis Shares important implications for model development and data analysis Can serve as reference for public health and biomedical research and as a text for use in courses on causal inference at the graduate level

Autor*in

Ding-Geng (Din) Chen

Themen in »Innovative Statistical Methods for Public Health Data«

Causal inference Health surveillance Incomplete or missing data Public health statistics Standardization and decomposition analysis (SDA) Statistics biomedical research

Stimmen zu »Innovative Statistical Methods for Public Health Data«

“The book is a compilation of new developments in statistical methods and applications relevant in public health research. … The primary audience is statisticians and researchers in biomedical and public health research. … Each chapter ends with a set of references for further reading. … This is an excellent book, with chapters addressing innovative statistical methods for specific statistical situations, targeted at researchers in the biomedical or public health fields.” (Kamesh Sivagnanam, Doody’s Book Reviews, January, 2016)

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