Pages that link to "Item:Q5120923"

The following pages link to An approach to model clustered survival data with dependent censoring (Q5120923):

Displaying 20 items.

• Factor copula models for right-censored clustered survival data (Q825281) (← links)
• A copula-based Markov chain model for serially dependent event times with a dependent terminal event (Q2068940) (← links)
• Multivariate failure time distributions derived from shared frailty and copulas (Q2068954) (← links)
• Accounting for drop-out using inverse probability censoring weights in longitudinal clustered data with informative cluster size (Q2135387) (← links)
• Meta-analysis of individual patient data with semi-competing risks under the Weibull joint frailty-copula model (Q2228211) (← links)
• Generalized inverse-Gaussian frailty models with application to TARGET neuroblastoma data (Q2230877) (← links)
• Yang and Prentice model with piecewise exponential baseline distribution for modeling lifetime data with crossing survival curves (Q2233649) (← links)
• Integrated likelihoods in parametric survival models for highly clustered censored data (Q2398457) (← links)
• A Frailty Model for Informative Censoring (Q3078981) (← links)
• Simulation study of the glmm method applied to the analysis of clustered survival data (Q4347014) (← links)
• Efficiency of independence working analysis of correlated survival data with general cluster size (Q4671013) (← links)
• Penalized Cox regression with a five-parameter spline model (Q5078865) (← links)
• A novel method for joint modeling of survival data and count data for both simple randomized and cluster randomized data (Q5078899) (← links)
• Modelling hierarchical clustered censored data with the hierarchical Kendall copula (Q5107579) (← links)
• A NEW MULTILEVEL MODELING APPROACH FOR CLUSTERED SURVIVAL DATA (Q5118576) (← links)
• (Q5886018) (← links)
• Generalized Birnbaum–Saunders mixture cure frailty model: inferential method and an application to bone marrow transplant data (Q6141743) (← links)
• The Pareto type I joint frailty-copula model for clustered bivariate survival data (Q6562748) (← links)
• Clayton copula for survival data with dependent censoring: an application to a tuberculosis treatment adherence data (Q6626938) (← links)
• Bayesian parametric estimation based on left-truncated competing risks data under bivariate Clayton copula models (Q6643337) (← links)