Simultaneously modelling censored survival data and repeatedly measured covariates: a Gibbs sampling approach.
about
Missing data methods in longitudinal studies: a reviewA joint model for longitudinal measurements and survival data in the presence of multiple failure types.A Bayesian approach to joint analysis of multivariate longitudinal data and parametric accelerated failure time.Simultaneous analysis of quality of life and survival data.Techniques for incorporating longitudinal measurements into analyses of survival data from clinical trials.A semiparametric likelihood approach to joint modeling of longitudinal and time-to-event data.Joint modeling of survival and longitudinal non-survival data: current methods and issues. Report of the DIA Bayesian joint modeling working groupJoint modeling of two longitudinal outcomes and competing risk data.A Bayesian semiparametric joint hierarchical model for longitudinal and survival data.Bayesian hierarchical model for multiple repeated measures and survival data: an application to Parkinson's diseaseAssessing model fit in joint models of longitudinal and survival data with applications to cancer clinical trials.Prediction of transplant-free survival in idiopathic pulmonary fibrosis patients using joint models for event times and mixed multivariate longitudinal data.Joint modeling of longitudinal health-related quality of life data and survival.Joint Analyses of Longitudinal and Time-to-Event Data in Research on Aging: Implications for Predicting Health and Survival.Bayesian nonparametric mixed-effects joint model for longitudinal-competing risks data analysis in presence of multiple data features.Joint models for multivariate longitudinal and multivariate survival data.Bayesian joint modeling of longitudinal and spatial survival AIDS data.Dynamic prediction of recurrent events data by landmarking with application to a follow-up study of patients after kidney transplant.Stochastic model for analysis of longitudinal data on aging and mortality.Joint modeling of longitudinal zero-inflated count and time-to-event data: A Bayesian perspective.Semiparametric approaches for joint modeling of longitudinal and survival data with time-varying coefficients.Performance of joint modelling of time-to-event data with time-dependent predictors: an assessment based on transition to psychosis data.Simultaneous inference for semiparametric mixed-effects joint models with skew distribution and covariate measurement error for longitudinal competing risks data analysis.Survival analysis using auxiliary variables via multiple imputation, with application to AIDS clinical trial data.Estimating cycle pregnancy probability with incomplete data in contraceptive studies.Robust joint modeling of longitudinal measurements and competing risks failure time dataA Bayesian approach to joint analysis of longitudinal measurements and competing risks failure time data.Basic concepts and methods for joint models of longitudinal and survival data.A general joint model for longitudinal measurements and competing risks survival data with heterogeneous random effects.Joint modeling of multivariate longitudinal data and the dropout process in a competing risk setting: application to ICU dataPrediction of Conversion to Alzheimer's Disease with Longitudinal Measures and Time-To-Event Data.Dynamic predictions and prospective accuracy in joint models for longitudinal and time-to-event data.Development and validation of decision rules to guide frequency of monitoring CD4 cell count in HIV-1 infection before starting antiretroviral therapyJoint modelling of longitudinal and time-to-event data with application to predicting abdominal aortic aneurysm growth and ruptureA joint model of longitudinal and competing risks survival data with heterogeneous random effects and outlying longitudinal measurementsBayesian influence measures for joint models for longitudinal and survival data.The quadratic hazard model for analyzing longitudinal data on aging, health, and the life span.Longitudinal data analysis with non-ignorable missing dataJoint model for a diagnostic test without a gold standard in the presence of a dependent terminal event.A joint-modeling approach to assess the impact of biomarker variability on the risk of developing clinical outcome.
P2860
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P2860
Simultaneously modelling censored survival data and repeatedly measured covariates: a Gibbs sampling approach.
description
1996 nî lūn-bûn
@nan
1996年の論文
@ja
1996年論文
@yue
1996年論文
@zh-hant
1996年論文
@zh-hk
1996年論文
@zh-mo
1996年論文
@zh-tw
1996年论文
@wuu
1996年论文
@zh
1996年论文
@zh-cn
name
Simultaneously modelling censo ...... es: a Gibbs sampling approach.
@en
type
label
Simultaneously modelling censo ...... es: a Gibbs sampling approach.
@en
prefLabel
Simultaneously modelling censo ...... es: a Gibbs sampling approach.
@en
P1476
Simultaneously modelling censo ...... es: a Gibbs sampling approach.
@en
P2093
P304
P356
10.1002/(SICI)1097-0258(19960815)15:15<1663::AID-SIM294>3.0.CO;2-1
P407
P577
1996-08-01T00:00:00Z