Statistical Methods for Dynamic Disease Screening and Spatio-Temporal Disease Surveillance.

Author
Qiu, Peihua [Browse]
Format
Book
Language
English
Εdition
1st ed.
Published/​Created
  • Milton : CRC Press LLC, 2024.
  • ©2024.
Description
1 online resource (346 pages)

Details

Series
Chapman and Hall/CRC Biostatistics Series [More in this series]
Summary note
Disease screening and disease surveillance (DSDS) constitute two critical areas in public health, each presenting distinctive challenges primarily due to their sequential decision-making nature and complex data structures. Explores numerous recent analytic methodologies that enhance traditional techniques.
Source of description
Description based on publisher supplied metadata and other sources.
Contents
  • Cover
  • Half Title
  • Series Page
  • Title Page
  • Copyright Page
  • Dedication
  • Contents
  • Preface
  • About the Author
  • 1. Introduction
  • 1.1. Disease and Disease Screening
  • 1.2. Disease Surveillance
  • 1.3. Organization of the Book
  • 1.4. Exercises
  • 2. Basic Statistical Concepts and Methods
  • 2.1. Population and Population Distribution
  • 2.2. Important Parametric Distributions
  • 2.2.1. Important Discrete Distributions
  • 2.2.2. Important Continuous Distributions
  • 2.3. Data and Data Description
  • 2.4. Parametric Statistical Inferences
  • 2.4.1. Point Estimation and Sampling Distribution
  • 2.4.2. Maximum Likelihood Estimation and Least Squares Estimation
  • 2.4.3. Confidence Intervals and Hypothesis Testing
  • 2.4.4. The Delta Method and the Bootstrap Method
  • 2.5. Nonparametric Statistical Inferences
  • 2.5.1. Order Statistics and Their Properties
  • 2.5.2. Goodness-of-Fit Tests
  • 2.5.3. Rank Tests
  • 2.5.4. Nonparametric Density Estimation
  • 2.5.5. Nonparametric Regression Analysis
  • 2.6. Longitudinal Data Analysis
  • 2.6.1. Linear Mixed-Effects Modeling
  • 2.6.2. Nonparametric Mixed-Effects Modeling
  • 2.7. Parametric Spatio-Temporal Data Analysis
  • 2.8. Exercises
  • 3. Basic Statistical Process Control Concepts and Methods
  • 3.1. Basic Concepts and Methods of Statistical Process Control
  • 3.1.1. Some Basic SPC Concepts
  • 3.1.2. Shewhart Charts
  • 3.1.3. CUSUM Charts
  • 3.1.4. EWMA Charts
  • 3.1.5. CPD Charts
  • 3.2. Self-Starting and Adaptive Control Charts
  • 3.2.1. Self-Starting Control Charts
  • 3.2.2. Adaptive Control Charts
  • 3.3. Nonparametric Control Charts
  • 3.3.1. Univariate Nonparametric Control Charts
  • 3.3.2. Multivariate Nonparametric Control Charts
  • 3.4. Control Charts for Monitoring Processes with Serially Correlated Data
  • 3.5. Exercises
  • 4. Disease Screening by Dynamic Screening Systems.
  • 4.1. Introduction
  • 4.2. Univariate Dynamic Screening System for Disease Screening
  • 4.2.1. Estimation of the Regular Longitudinal Pattern
  • 4.2.2. Data Standardization for Disease Early Detection
  • 4.2.3. Sequential Monitoring of the Observed Disease Risk Factor for Disease Early Detection
  • 4.3. Multivariate Dynamic Screening System for Disease Screening
  • 4.3.1. Estimation of the Regular Longitudinal Pattern
  • 4.3.2. Data Standardization for Disease Early Detection
  • 4.3.3. Online Monitoring of Multiple Disease Risk Factors for Disease Early Detection
  • 4.4. Cases with Serially Correlated and Nonparametrically Distributed Data
  • 4.5. Robust Disease Screening by Estimation of Longitudinal Data Distribution
  • 4.5.1. Description and Estimation of the Regular Longitudinal Pattern
  • 4.5.2. Online Monitoring of the Observed Disease Risk Factor
  • 4.6. Some Discussions
  • 4.7. Exercises
  • 5. Disease Screening by Online Disease Risk Monitoring
  • 5.1. Introduction
  • 5.2. Quantification of Disease Risk
  • 5.3. Disease Screening by Online Monitoring of Quantified Disease Risks
  • 5.4. Disease Screening by Joint Modeling of Survival and Longitudinal Data
  • 5.4.1. Joint Modeling of Survival and Longitudinal Data
  • 5.4.2. Dynamic Disease Screening
  • 5.5. Disease Screening by Variable Selection
  • 5.6. Some Discussions
  • 5.7. Exercises
  • 6. R Package DySS for Dynamic Disease Screening
  • 6.1. Introduction
  • 6.2. Major Functions in the R Package DySS
  • 6.3. Some Demonstrations
  • 6.3.1. Estimation of the Regular Longitudinal Pattern of the Disease Risk Factors
  • 6.3.2. Disease Screening by Sequentially Monitoring the Observed Disease Risk Factors
  • 6.3.3. Evaluation of the Disease Screening Methods
  • 6.4. Exercises
  • 7. Disease Surveillance by Some Retrospective Methods
  • 7.1. Introduction.
  • 7.2. Detection of Space-Time Interaction by the Knox Test
  • 7.3. Scan Statistics for Disease Cluster Detection
  • 7.4. Generalized Linear Modeling for Disease Cluster Detection
  • 7.5. Some Discussions
  • 7.6. Exercises
  • 8. Disease Surveillance by Nonparametric Spatio-Temporal Data Monitoring
  • 8.1. Introduction
  • 8.2. Nonparametric Spatio-Temporal Data Modeling
  • 8.2.1. A Nonparametric Spatio-Temporal Regression Model
  • 8.2.2. Estimation of the Mean Function When the Spatio-Temporal Data Correlation is Ignored
  • 8.2.3. Estimation of the Variance and Covariance Functions
  • 8.2.4. Estimation of the Mean Function with the Spatio-Temporal Data Correlation Accommodated
  • 8.3. Disease Surveillance by Nonparametric Spatio-Temporal Data Modeling
  • 8.4. Disease Surveillance by Exponentially Weighted Spatial LASSO
  • 8.5. Disease Surveillance by Using Covariate Information
  • 8.5.1. Estimation of the Regular Spatio-Temporal Pattern
  • 8.5.2. Spatio-Temporal Disease Surveillance by Using Covariate Information
  • 8.6. Some Discussions
  • 8.7. Exercises
  • 9. R Package SpTe2M for Nonparametric Spatio-Temporal Data Modeling and Monitoring
  • 9.1. Introduction
  • 9.2. Major Functions in the R Package SpTe2M
  • 9.3. Some Demonstrations
  • 9.3.1. Spatio-Temporal Data Modeling
  • 9.3.2. Spatio-Temporal Data Monitoring
  • 9.4. Exercises
  • Bibliography
  • Index.
ISBN
  • 1-04-002672-9
  • 1-003-13815-2
  • 1-04-002673-7
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