Search
Search Results
-
Bayesian semiparametric joint model of multivariate longitudinal and survival data with dependent censoring
We consider a novel class of semiparametric joint models for multivariate longitudinal and survival data with dependent censoring. In these models,...
-
A Bayesian Joint Model of Longitudinal Kidney Disease Progression, Recurrent Cardiovascular Events, and Terminal Event in Patients with Chronic Kidney Disease
Nearly 15% (37 million) of adults in the United States (US) have chronic kidney disease (CKD). The longitudinal decline of kidney function is...
-
Incorporating delayed entry into the joint frailty model for recurrent events and a terminal event
In studies of recurrent events, joint modeling approaches are often needed to allow for potential dependent censoring by a terminal event such as...
-
Bayesian joint quantile autoregression
Quantile regression continues to increase in usage, providing a useful alternative to customary mean regression. Primary implementation takes the...
-
Joint Bayesian longitudinal models for mixed outcome types and associated model selection techniques
Motivated by data measuring progression of leishmaniosis in a cohort of US dogs, we develop a Bayesian longitudinal model with autoregressive errors...
-
Joint Distributions
This chapter introduces the distribution of functions of several random variables. The Jacobian of matrix transformation is described and its...
-
Empirical likelihood MLE for joint modeling right censored survival data with longitudinal covariates
Up to now, almost all existing methods for joint modeling survival data and longitudinal data rely on parametric/semiparametric assumptions on...
-
A Bayesian quantile joint modeling of multivariate longitudinal and time-to-event data
Linear mixed models are traditionally used for jointly modeling (multivariate) longitudinal outcomes and event-time(s). However, when the outcomes...
-
Joint Modeling of Geometric Features of Longitudinal Process and Discrete Survival Time Measured on Nested Timescales: An Application to Fecundity Studies
In biomedical studies, longitudinal processes are collected till time-to-event, sometimes on nested timescales (example, days within months). Most of...
-
Joint Spatial Modeling Bridges the Gap Between Disparate Disease Surveillance and Population Monitoring Efforts Informing Conservation of At-risk Bat Species
White-Nose Syndrome (WNS) is a wildlife disease that has decimated hibernating bats since its introduction in North America in 2006. As the disease...
-
Assessing the numerical integration of dynamic prediction formulas using the exact expressions under the joint frailty-copula model
Joint models allow survival outcomes of a patient to be dynamically predictable based on intermediate events observed after treatment. The existing...
-
Joint Linear Modeling of Mixed Data and Its Application to Email Analysis
We present a new model in Social Networks which allows experts in this field to analyze social networks. In this paper, a joint random effect linear...
-
Joint Models for Longitudinal Zero-Inflated Overdispersed Binomial and Normal Responses
In this paper, we propose joint random effects models for longitudinal mixed overdispersion binomial and normal responses where the overdispersion...
-
Joint modeling of generalized scale-change models for recurrent event and failure time data
Recurrent event and failure time data arise frequently in many clinical and observational studies. In this article, we propose a joint modeling of...
-
Bayesian Design of Clinical Trials Using Joint Cure Rate Models for Longitudinal and Time-to-Event Data
For clinical trial design and analysis, there has been extensive work related to using joint models for longitudinal and time-to-event data without a...
-
Bayesian and Likelihood Estimation in Two Inverse Pareto Populations Under Joint Progressive Censoring
In the era of growing technologies and demand for more reliable products, a comparative study of products from various manufacturing units has become...
-
Joint modeling for longitudinal covariate and binary outcome via h-likelihood
Joint modeling techniques of longitudinal covariates and binary outcomes have attracted considerable attention in medical research. The basic...
-
Quantile regression via the EM algorithm for joint modeling of mixed discrete and continuous data based on Gaussian copula
In this paper, we develop a joint quantile regression model for correlated mixed discrete and continuous data using Gaussian copula. Our approach...
-
Random Graphical Model of Microbiome Interactions in Related Environments
The microbiome constitutes a complex microbial ecology of interacting components that regulates important pathways in the host. Most microbial...
-
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...
