Innovative statistical methods for public health data4h[electronic resource] / Ding-Geng (Din) Chen, Jeffrey Wilson, editors. [electronic resource]
Chen, Ding-Geng, editor.; Wilson, Jeffrey, editor.
2015
RA652.2.P82
Available Online

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Title Innovative statistical methods for public health data4h[electronic resource] / Ding-Geng (Din) Chen, Jeffrey Wilson, editors. [electronic resource]
ISBN 9783319185361 electronic book
3319185365 electronic book
9783319185354
DOI https://doi.org/10.1007/978-3-319-18536-1
Published Cham ; New York : Springer, [2015]
Copyright ©2015
Language English
Description 1 online resource.
Item Number 10.1007/978-3-319-18536-1 doi
Call Number RA652.2.P82
Dewey Decimal Classification 614.407/27
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.
Bibliography, etc. Note Include bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (viewed September 4, 2015)
Added Author Chen, Ding-Geng, editor.
Wilson, Jeffrey, editor.
Series ICSA book series in statistics.
Available in Other Form Print version: 9783319185354
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Record Appears in Online Resources > Ebooks
All Resources
Part 1: Modelling Clustered Data
Methods for Analyzing Secondary Outcomes in Public Health Case Control Studies
Controlling for Population Density Using Clustering and Data Weighting Techniques When Examining Social Health and Welfare Problems
On the Inference of Partially Correlated Data with Applications to Public Health Issues
Modeling Time-Dependent Covariates in Longitudinal Data Analyses
Solving Probabilistic Discrete Event Systems with Moore-Penrose Generalized Inverse Matrix Method to Extract Longitudinal Characteristics from Cross-Sectional Survey Data
Part II: Modelling Incomplete or Missing Data
On the Effects of Structural Zeros in Regression Models
Modeling Based on Progressively Type-I Interval Censored Sample
Techniques for Analyzing Incomplete Data in Public Health Research
A Continuous Latent Factor Model for Non-ignorable Missing Data
Part III: Healthcare Research Models
Health Surveillance
Standardization and Decomposition Analysis: A Useful Analytical Method for Outcome Difference, Inequality and Disparity Studies
Cusp Catastrophe Modeling in Medical and Health Research
On Ranked Set Sampling Variation and its Applications to Public Health Research
Weighted Multiple Testing Correction for Correlated Endpoints in Survival Data
Meta-analytic Methods for Public Health Research.

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