Innovative Statistical Methods for Public Health Data edited by Ding-Geng (Din) Chen, Jeffrey Wilson.

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 analy...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Chen, Ding-Geng (Din) (Editor), Wilson, Jeffrey (Editor)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2015.
Edition:1st ed. 2015.
Series:ICSA Book Series in Statistics,
Springer eBook Collection.
Subjects:
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Description
Summary: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.
Physical Description:XIV, 351 p. 45 illus., 22 illus. in color. online resource.
ISBN:9783319185361
ISSN:2199-0980
DOI:10.1007/978-3-319-18536-1