censored data

censored data

[¦sen·sərd ′dad·ə]
(statistics)
Observations collected by determining in advance whether to record only a specified number of the smallest or largest values, or of the remaining values in a sample of a particular size.
References in periodicals archive ?
Two methods can be used to estimate the proportion of the defective subpopulation - one is based on censored data [2] and another is based on truncated data [2, 12, 16].
The effort substantially decreased the amount of censored data; for example, THC censored data went from 80% to ~ 20%.
Marshall-Olkin extended Weibull distribution and its application to censored data.
A hallmark of ROC curves constructed with censored data is the straight line between the point on the curve corresponding to the threshold concentration for censoring and the top right hand corner.
We modeled the relationship between time to predation and environmental variables with a Cox proportional hazards analysis that accounts for censored data.
Raqab and Madi [4] discussed the Bayesian predictive methods for the total time on test using doubly censored data with a Rayleigh distribution and the scale parameter and applied the methods to a real data set that represented the deep-groove ball bearing failure times.
In addition, for patient survival, the censored data included switching to hemodialysis, and for technique survival, death as the censored data.
Scant attention is then devoted to five data analysis techniques: stochastic frontiers, truncated data analysis, censored data analysis, duration data analysis, and high dimensional data visualization.
Reference [6] studied Bayesian parameter and reliability estimate of Weibull failure time distribution; reference [7] studied the approximate Bayesian estimates for the Weibull reliability function and hazard rate from censored data by employing a new method that has the potential of reducing the number of terms in Lindley procedure.
acq] (incorporating censored data due to locational error thresholds) using logistic regression to estimate resource selection functions, 3) use inverse weighting of [P.