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Innovative Statistical Methods for Public Health Data

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Cover of 'Innovative Statistical Methods for Public Health Data'

Table of Contents

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    Book Overview
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    Chapter 1 Methods for Analyzing Secondary Outcomes in Public Health Case–Control Studies
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    Chapter 2 Controlling for Population Density Using Clustering and Data Weighting Techniques When Examining Social Health and Welfare Problems
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    Chapter 3 On the Inference of Partially Correlated Data with Applications to Public Health Issues
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    Chapter 4 Modeling Time-Dependent Covariates in Longitudinal Data Analyses
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    Chapter 5 Solving Probabilistic Discrete Event Systems with Moore–Penrose Generalized Inverse Matrix Method to Extract Longitudinal Characteristics from Cross-Sectional Survey Data
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    Chapter 6 On the Effects of Structural Zeros in Regression Models
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    Chapter 7 Modeling Based on Progressively Type-I Interval Censored Sample
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    Chapter 8 Techniques for Analyzing Incomplete Data in Public Health Research
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    Chapter 9 A Continuous Latent Factor Model for Non-ignorable Missing Data
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    Chapter 10 Health Surveillance
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    Chapter 11 Standardization and Decomposition Analysis: A Useful Analytical Method for Outcome Difference, Inequality and Disparity Studies
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    Chapter 12 Cusp Catastrophe Modeling in Medical and Health Research
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    Chapter 13 On Ranked Set Sampling Variation and Its Applications to Public Health Research
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    Chapter 14 Weighted Multiple Testing Correction for Correlated Endpoints in Survival Data
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    Chapter 15 Meta-Analytic Methods for Public Health Research
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