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Binary Data
Many of the results derived under the assumption that observations are continuously distributed extend to dichotomous and categorical responses....
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A Frailty Model for Semi-competing Risk Data with Applications to Colon Cancer
In semi-competing risks (which generalizes the competing risks scenario), a subject may experience both terminal and non-terminal events, usually...
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Graphical Models for Categorical Data
This chapter describes the use of graphical models to analyse categorical data. After defining the (conditional) independence graph, the core...
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Data Science Solutions with Python Fast and Scalable Models Using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn
Apply supervised and unsupervised learning to solve practical and real-world big data problems. This book teaches you how to engineer features,...
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On Bivariate Dynamic Survival Extropy and Its Estimation
Recently (Lad and Sanfilippo
2015 ) proposed extropy as a complement dual of Shannon’s entropy in the univariate case. This paper extended the concept...
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A review of h-likelihood for survival analysis
Statistical models with unobservable random variables such as random-effect models have been recently studied for analyzing data of complex types...
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Flexible Modeling of Frailty Effects in Clustered Survival Data
Survival data that have a multivariate structure occur in many health sciences including biomedical research, epidemiology studies and, clinical...
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Integrating Different Data Sources Using a Bayesian Hierarchical Model to Unveil Glacial Refugia
Rapid anthropogenic climate change has elevated the interest in studying the biotic responses of species during the Last Glacial Maximum. During this...
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Laplace regression with clustered censored data
In survival analysis, data may be correlated or clustered, because of some features such as shared genes and environmental background. A common...
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Foundations I: Introductory Data Analysis with R
In disciplinary research—from Anthropology to Zoology (and every discipline in between!)—studies produce data from multiple variables. Most research...
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Marginal Structural Illness-Death Models for Semi-competing Risks Data
The three-state illness-death model has been established as a general approach for regression analysis of semi-competing risks data. For...
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Non-parametric Frailty Model for the Natural History of Prostate Cancer; Using Data from a Screening Trial
Mixed-effects models for survival, known as frailty models, can be used to capture individual or cluster-specific unobserved heterogeneity. A common...
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Statistical Challenges for Causal Inference Using Time-to-Event Real-World Data
Real-world data (RWD) have been increasingly used in drug development, e.g., for indirect comparisons of treatments in real-world settings and...
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Multivariate Leimkuhler Curve: Properties and Applications to Analysis of Bibliometric Data
The Leimkuhler curve has established itself as an efficient tool in the analysis and comparison of concentration of bibliometric measures of...
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Model averaging for right censored data with measurement error
This paper studies a novel model averaging estimation issue for linear regression models when the responses are right censored and the covariates are...
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Diagnostic Test for Realized Missingness in Mixed-type Data
A frequent concern in analyzing incomplete multivariate measurements in mixed categorical and quantitative scales is whether missing completely at...
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Joint Analysis of Longitudinal and Time-to-Event Data
The longitudinal and time-to-event data are two kinds of common data generated from various clinical trials across different therapeutic areas. Joint...
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Accelerated failure time models for recurrent event data analysis and joint modeling
There are two commonly encountered problems in survival analysis: (a) recurrent event data analysis, where an individual may experience an event...
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Change Point Detection in Length-Biased Weibull Distribution for Random Censored Data Based on Modified Information Criterion
In this article, we study the change point problem of length-biased Weibull distribution under the scenario of random censorship. We construct the...
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A class of models for large zero-inflated spatial data
Spatially correlated data with an excess of zeros, usually referred to as zero-inflated spatial data, arise in many disciplines. Examples include...
