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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...
TECHNOLOGICAL ACQUISITIONS AND THE INNOVATION PERFORMANCE OF ACQUIRING FIRMS: A LONGITUDINAL STUDY
TECHNOLOGICAL ACQUISITIONS INNOVATION PERFORMANCE ACQUIRING FIRMS LONGITUDINAL STUDY
2015/7/3
This paper examines the impact of acquisitions on the subsequent innovation performance of acquiring firms in the chemicals industry. We distinguish between technological acquisitions, acquisitions in...
SOMETHING OLD,SOMETHING NEW:A LONGITUDINAL STUDY OF SEARCH BEHAVIOR AND NEW PRODUCT INTRODUCTION
SOMETHING OLD SOMETHING NEW LONGITUDINAL STUDY SEARCH BEHAVIOR NEW PRODUCT INTRODUCTION
2015/7/3
We examine how firms search, or solve problems, to create new products. According to organizational learning research, firms position themselves in a unidimensional search space that spans a spectrum ...
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...
Workforce participation among international medical graduates in the National Health Service of England: a retrospective longitudinal study
workforce participation international medical graduates the National Health Service of England a retrospective longitudinal study
2009/9/27
Adjusting workforce participation by country of qualification can improve estimates of the number of medical school places needed to balance supply with demand. Developing countries undergoing strong ...
Is satisfaction a direct predictor of nursing turnover? Modelling the relationship between satisfaction, expressed intention and behaviour in a longitudinal cohort study
nursing turnover satisfaction expressed intention behaviour a longitudinal cohort study
2009/9/27
Results partially support the theory of planned behaviour. Intentions expressed by nurses are stronger predictors of working as a nurse than job satisfaction. Retention strategies should focus on iden...
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...