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.
Author(s): Ding-Geng (Din) Chen, Jeffrey Wilson (eds.)
Series: ICSA Book Series in Statistics
Edition: 1
Publisher: Springer International Publishing
Year: 2015
Language: English
Pages: XIV, 351
Tags: Statistics for Life Sciences, Medicine, Health Sciences; Public Health; Laboratory Medicine
Front Matter....Pages i-xiv
Front Matter....Pages 1-1
Methods for Analyzing Secondary Outcomes in Public Health Case–Control Studies....Pages 3-15
Controlling for Population Density Using Clustering and Data Weighting Techniques When Examining Social Health and Welfare Problems....Pages 17-30
On the Inference of Partially Correlated Data with Applications to Public Health Issues....Pages 31-55
Modeling Time-Dependent Covariates in Longitudinal Data Analyses....Pages 57-79
Solving Probabilistic Discrete Event Systems with Moore–Penrose Generalized Inverse Matrix Method to Extract Longitudinal Characteristics from Cross-Sectional Survey Data....Pages 81-94
Front Matter....Pages 95-95
On the Effects of Structural Zeros in Regression Models....Pages 97-115
Modeling Based on Progressively Type-I Interval Censored Sample....Pages 117-151
Techniques for Analyzing Incomplete Data in Public Health Research....Pages 153-171
A Continuous Latent Factor Model for Non-ignorable Missing Data....Pages 173-199
Front Matter....Pages 201-201
Health Surveillance....Pages 203-249
Standardization and Decomposition Analysis: A Useful Analytical Method for Outcome Difference, Inequality and Disparity Studies....Pages 251-264
Cusp Catastrophe Modeling in Medical and Health Research....Pages 265-290
On Ranked Set Sampling Variation and Its Applications to Public Health Research....Pages 291-313
Weighted Multiple Testing Correction for Correlated Endpoints in Survival Data....Pages 315-324
Meta-Analytic Methods for Public Health Research....Pages 325-340
Back Matter....Pages 341-351
