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Monte-Carlo Simulation-Based Statistical Modeling

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Cover of 'Monte-Carlo Simulation-Based Statistical Modeling'

Table of Contents

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    Book Overview
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    Chapter 1 Joint Generation of Binary, Ordinal, Count, and Normal Data with Specified Marginal and Association Structures in Monte-Carlo Simulations
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    Chapter 2 Improving the Efficiency of the Monte-Carlo Methods Using Ranked Simulated Approach
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    Chapter 3 Normal and Non-normal Data Simulations for the Evaluation of Two-Sample Location Tests
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    Chapter 4 Anatomy of Correlational Magnitude Transformations in Latency and Discretization Contexts in Monte-Carlo Studies
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    Chapter 5 Monte-Carlo Simulation of Correlated Binary Responses
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    Chapter 6 Quantifying the Uncertainty in Optimal Experiment Schemes via Monte-Carlo Simulations
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    Chapter 7 Markov Chain Monte-Carlo Methods for Missing Data Under Ignorability Assumptions
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    Chapter 8 A Multiple Imputation Framework for Massive Multivariate Data of Different Variable Types: A Monte-Carlo Technique
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    Chapter 9 Hybrid Monte-Carlo in Multiple Missing Data Imputations with Application to a Bone Fracture Data
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    Chapter 10 Statistical Methodologies for Dealing with Incomplete Longitudinal Outcomes Due to Dropout Missing at Random
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    Chapter 11 Applications of Simulation for Missing Data Issues in Longitudinal Clinical Trials
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    Chapter 12 Application of Markov Chain Monte-Carlo Multiple Imputation Method to Deal with Missing Data from the Mechanism of MNAR in Sensitivity Analysis for a Longitudinal Clinical Trial
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    Chapter 13 Monte-Carlo Simulation in Modeling for Hierarchical Generalized Linear Mixed Models
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    Chapter 14 Monte-Carlo Methods in Financial Modeling
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    Chapter 15 Simulation Studies on the Effects of the Censoring Distribution Assumption in the Analysis of Interval-Censored Failure Time Data
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    Chapter 16 Robust Bayesian Hierarchical Model Using Monte-Carlo Simulation
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    Chapter 17 A Comparison of Bootstrap Confidence Intervals for Multi-level Longitudinal Data Using Monte-Carlo Simulation
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    Chapter 18 Bootstrap-Based LASSO-Type Selection to Build Generalized Additive Partially Linear Models for High-Dimensional Data
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    Chapter 19 Erratum to: Monte-Carlo Simulation-Based Statistical Modeling
Attention for Chapter 9: Hybrid Monte-Carlo in Multiple Missing Data Imputations with Application to a Bone Fracture Data
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Chapter title
Hybrid Monte-Carlo in Multiple Missing Data Imputations with Application to a Bone Fracture Data
Chapter number 9
Book title
Monte-Carlo Simulation-Based Statistical Modeling
Published by
Springer Singapore, February 2017
DOI 10.1007/978-981-10-3307-0_9
Book ISBNs
978-9-81-103306-3, 978-9-81-103307-0
Authors

Hui Xie

Editors

Ding-Geng (Din) Chen, John Dean Chen

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Unknown 1 100%
Readers by discipline Count As %
Business, Management and Accounting 1 100%

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