Innovative Statistical Methods for Public Health Data
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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| Other Authors: | , |
| Language: | English |
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Cham :
Springer International Publishing : Imprint: Springer,
2015.
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| Edition: | 1st ed. 2015. |
| Series: | ICSA Book Series in Statistics,
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| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-3-319-18536-1 |
Table of Contents:
- 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.