We investigate the use of follow-up samples of individuals to estimate survival curves from studies that are subject to right censoring from two sources: (i) early termination of the study, namely, administrative censoring, or (ii) censoring due to lost data prior to administrative censoring, so-called dropout. We assume that, for the full cohort of individuals, administrative censoring times a...

In this paper, we proposed the Bayesian estimation for parameter and reliability function of exponentiated gamma distribution under progressive type-II censored samples. The Bayes estimate are derived assumption independent prior by three different approximation methods namely Lindley’s approximation, Tierney-Kadane Markov Chain Monte Carlo methods. Further, comparison estimators with correspon...

We consider a regression analysis of multivariate interval-censored failure time data where the censoring may be informative. To address this, an approximated maximum likelihood estimation approach is proposed under general class semiparametric transformation models, and in method, frailty employed to characterize informative interval censoring. For implementation we develop novel EM algorithm ...

We extend Cox’s classical regression model to accomodate partially informative censored data. In this type of data, each observation is the minimum of one lifetime and two censoring times. The survival function of one of these censoring times is a power of the survival function of the lifetime. We call this the informative censoring time. The distribution of the other censoring time has no rela...

Subject motion degrades the quality of task functional magnetic resonance imaging (fMRI) data. Here, we test two classes of methods to counteract the effects of motion in task fMRI data: (1) a variety of motion regressions and (2) motion censoring ("motion scrubbing"). In motion regression, various regressors based on realignment estimates were included as nuisance regressors in general linear ...