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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
Attention for Chapter 8: Techniques for Analyzing Incomplete Data in Public Health Research
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Citations

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Chapter title
Techniques for Analyzing Incomplete Data in Public Health Research
Chapter number 8
Book title
Innovative Statistical Methods for Public Health Data
Published by
Springer International Publishing, January 2015
DOI 10.1007/978-3-319-18536-1_8
Book ISBNs
978-3-31-918535-4, 978-3-31-918536-1
Authors

Valerie Pare, Ofer Harel

Editors

Ding-Geng (Din) Chen, Jeffrey Wilson

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 67%
Professor 1 33%
Student > Doctoral Student 1 33%
Readers by discipline Count As %
Nursing and Health Professions 2 67%
Medicine and Dentistry 1 33%

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