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Joint Modeling and Clustering Paired Generalized Longitudinal Trajectories with Application to Cocaine Abuse Treatment Data
Clustering Functional data analysis Exponential family Joint modeling
2016/1/26
In a cocaine dependence treatment study, we have paired binary longitudinal tra-jectories that record the cocaine use patterns of each patient before and after a treat-ment. To better understand the d...
Joint Modeling and Clustering Paired Generalized Longitudinal Trajectories with Application to Cocaine Abuse Treatment Data
Clustering functional data analysis exponential family joint modeling EM algorithm
2016/1/20
In a cocaine dependence treatment study, we have paired binary longitudinal tra-jectories that record the cocaine use patterns of each patient before and after a treat-ment. To better understand the d...
Combining Dynamic Predictions from Joint Models for Longitudinal and Time-to-Event Data using Bayesian Model Averaging
Prognostic Modeling Risk Prediction
2013/4/27
The joint modeling of longitudinal and time-to-event data is an active area of statistics research that has received a lot of attention in the recent years. More recently, a new and attractive applica...
Modeling left-truncated and right-censored survival data with longitudinal covariates
Likelihood approach semiparametric efficiency biased sample EM algorithm Monte Carlo integration
2012/11/23
There is a surge in medical follow-up studies that include longitudinal covariates in the modeling of survival data. So far, the focus has been largely on right-censored survival data. We consider sur...
Bayesian inference on dependence in multivariate longitudinal data
Cholesky decomposition covariance matrix moment-matching oxidative stress random effects shrinkage prior.
2012/9/17
In many applications, it is of interest to assess the dependence structure in multivariate longitudinal data. Discovering such dependence is challenging
due to the dimensionality involved. By concate...
Nested hidden Markov chains for modeling dynamic unobserved heterogeneity in multilevel longitudinal data
composite likelihood EM algorithm latent Markov model pairwise likelihood
2012/9/17
In the context of multilevel longitudinal data, where sample units are collected in clusters, an important aspect that should be accounted for is the unobserved heterogeneity between sample units and ...
HIV dynamics and natural history studies: Joint modeling with doubly interval-censored event time and infrequent longitudinal data
AIDS antiviral treatment interval censoring semiparametric regression
2011/6/16
Hepatitis C virus (HCV) coinfection has become one of the most
challenging clinical situations to manage in HIV-infected patients.
Recently the effect of HCV coinfection on HIV dynamics following
i...
Mixed models for longitudinal left-censored repeated measures
Mixed model Repeated measures Left-censoring SAS proc NLMIXED HIV infection
2010/4/29
Longitudinal studies could be complicated by left-censored repeated measures. For example, in Human Immunodeficiency Virus infection, there is a detection limit of the assay used to quantify the plasm...
Covariate adjusted functional principal components analysis for longitudinal data
Functional data analysis functional principal componentsanalysis local linear regression longitudinal data analysis smoothing sparse data
2010/3/11
Classical multivariate principal component analysis has been extended
to functional data and termed functional principal component
analysis (FPCA). Most existing FPCA approaches do not accommodate
...
Longitudinal Data with Follow-up Truncated by Death:Match the Analysis Method to Research
Censoring generalized estimating equations longitudinal data missing data quality of life random effects models truncation by death
2010/3/9
Diverse analysis approaches have been proposed to distin-
guish data missing due to death from nonresponse, and to summarize
trajectories of longitudinal data truncated by death. We demonstrate
how...
Prediction of Pregnancy: A Joint Model for Longitudinal and Binary Data
joint model mixed linear model generalized linear model longitudinal data binary data
2009/9/24
We consider the problem of predicting the achievement of successful pregnancy, in a population of women undergoing treatment for infertility, based on longitudinal measurements o...
Statistical Analysis for Longitudinal Counting Data in the Presence of a Covariate Considering Different
Statistical Analysis Longitudinal Counting Data
2009/9/17
Statistical Analysis for Longitudinal Counting Data in the Presence of a Covariate Considering Different "Frailty" Models。
Controlling for individual heterogeneity in longitudinal models, with applications to student achievement
longitudinal data analysis random effects models fixed effects models omitted variables
2009/9/16
Longitudinal data tracking repeated measurements on individuals are highly valued for research because they offer controls for unmeasured individual heterogeneity that might otherwise bias results. Ra...
Causal inference in longitudinal studies with history-restricted marginal structural models
causal inference counterfactual marginal structural model longitudinal study IPTW G-computation Double Robust
2009/9/16
A new class of Marginal Structural Models (MSMs), History-Restricted MSMs (HRMSMs), was recently introduced for longitudinal data for the purpose of defining causal parameters which may often be bette...
Explicit connections between longitudinal data analysis and kernel machines
Best linear unbiased prediction classification generalized linear mixed models machine learning linear mixed models reproducing kernel Hilbert spaces
2009/9/16
Two areas of research – longitudinal data analysis and kernel machines – have large, but mostly distinct, literatures. This article shows explicitly that both fields have much in common with each othe...