Titlebook: Emerging Topics in Modeling Interval-Censored Survival Data; Jianguo Sun,Ding-Geng Chen Book 2022 The Editor(s) (if applicable) and The Au

etidronate

Maximum Likelihood Estimation of Semiparametric Regression Models with Interval-Censored Dataobserved at an exact time point but is rather known to occur within a time interval induced by periodic examinations. We formulate the effects of potentially time-dependent covariates on the failure time through the semiparametric Cox proportional hazards model. We study nonparametric maximum likeli

Dappled

不發(fā)音

Copula Models and Diagnostics for Multivariate Interval-Censored Data from the non-fatal events are sometimes unobservable due to “interval-censoring” since the event status can only be determined at intermittent assessment times. In this chapter, we introduce a class of copula models to analyze multivariate interval-censored outcomes. It is a joint approach that dir

主講人

Sputum

男生戴手銬

Daily-Value

The ,: An R Package for Nonparametric Inference of Bivariate Interval-Censored Datainterval censoring that gives rise to bivariate interval-censored data. Nonparametric inference of bivariate interval-censored data focuses on estimation of the joint distribution function of event times or the joint survival function. The conventional nonparametric maximum likelihood estimator suff

狗舍

Joint Modeling for Longitudinal and Interval-Censored Survival Data: Application to IMPI Multi-Centewith the associated event times. These models are useful in two practical applications; firstly focusing on survival outcome whilst accounting for time-varying covariates measured with error and secondly focusing on the longitudinal outcome while controlling for informative censoring. The joint mode

Incorporate

細(xì)胞膜