## Monte-Carlo Simulation-Based Statistical ModelingThis book brings together expert researchers engaged in Monte-Carlo simulation-based statistical modeling, offering them a forum to present and discuss recent issues in methodological development as well as public health applications. It is divided into three parts, with the first providing an overview of Monte-Carlo techniques, the second focusing on missing data Monte-Carlo methods, and the third addressing Bayesian and general statistical modeling using Monte-Carlo simulations. The data and computer programs used here will also be made publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, and to readily apply them in their own research. Featuring highly topical content, the book has the potential to impact model development and data analyses across a wide spectrum of fields, and to spark further research in this direction. |

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### Contents

3 | |

17 | |

Normal and Nonnormal Data Simulations for the Evaluation of TwoSample Location Tests | 41 |

Anatomy of Correlational Magnitude Transformations in Latency and Discretization Contexts in MonteCarlo Studies | 59 |

MonteCarlo Simulation of Correlated Binary Responses | 85 |

Quantifying the Uncertainty in Optimal Experiment Schemes via MonteCarlo Simulations | 107 |

Part II MonteCarlo Methods in Missing Data | 127 |

Markov Chain MonteCarlo Methods for Missing Data Under Ignorability Assumptions | 129 |

Application of Markov Chain MonteCarlo Multiple Imputation Method to Deal with Missing Data from the Mechanism of MNAR in Sensitivity Anal... | 233 |

Part III MonteCarlo in Statistical Modellings and Applications | 253 |

MonteCarlo Simulation in Modeling for Hierarchical Generalized Linear Mixed Models | 255 |

MonteCarlo Methods in Financial Modeling | 285 |

Simulation Studies on the Effects of the Censoring Distribution Assumption in the Analysis of IntervalCensored Failure Time Data | 319 |

Robust Bayesian Hierarchical Model Using MonteCarlo Simulation | 347 |

A Comparison of Bootstrap Confidence Intervals for Multilevel Longitudinal Data Using MonteCarlo Simulation | 367 |

BootstrapBased LASSOType Selection to Build Generalized Additive Partially Linear Models for HighDimensional Data | 405 |

A MonteCarlo Technique | 143 |

Hybrid MonteCarlo in Multiple Missing Data Imputations with Application to a Bone Fracture Data | 163 |

Statistical Methodologies for Dealing with Incomplete Longitudinal Outcomes Due to Dropout Missing at Random | 179 |

Applications of Simulation for Missing Data Issues in Longitudinal Clinical Trials | 211 |

### Other editions - View all

Monte-Carlo Simulation-Based Statistical Modeling Ding-Geng (Din) Chen,John Dean Chen No preview available - 2017 |

Monte-Carlo Simulation-Based Statistical Modeling Ding-Geng (Din) Chen,John Dean Chen No preview available - 2018 |

Monte-Carlo Simulation-Based Statistical Modeling Ding-Geng Chen,John Dean Chen No preview available - 2017 |

### Common terms and phrases

ˆβ algorithm approach assumed assumption autocorrelation Bayesian bias binary data binary outcomes bootstrap chapter Chen clinical trial cluster coefficients computational conditional confidence interval convergence correlated binary covariance matrix covariates data analysis data set Demirtas denote density dichotomized discretization dropout fixed effects function Gibbs sampling GLIMMIX procedure GLMM hazard functions Hedeker inference iteration Journal logistic regression longitudinal data marginal Markov chain MCMC mean MI-GEE missing data missing values missingness mixed model MLIRT model MMRM MNAR Molenberghs Monte-Carlo methods Monte-Carlo simulation multiple imputation multivariate nonnormal nonparametric normal distribution observed optimal experiment scheme ordinal p-value parameter estimates penalized regression phi coefficient polychoric polynomials posterior predictors probability random effects random intercept random variables Rubin Samawi simulation study skewness specified standard deviation students per classroom t-test Table treatment two-stage bootstrap type I error variance vector Welch’s t-test WGEE Wilcoxon rank-sum test