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Because most of the subway vehicles system life distribution data is censored data, we use the survival analysis in the system time between failures to process censored data.
Fig. 2 Illustrating SR Method Table 1 Illustrating SR method Probability Interval Distribution Used for Simulation 0.25 100–200 Uniform 0.25 200–300 Uniform 0.25 300–400 Uniform 0.25 400–500 Triangular. Figure 2 is an example where 25%% of patients experienced death at day 100, 200, and 300 and from day 400 onwards the data is censored.
The Tobit model assumes that the distribution of data is censored normal and that the overall log-likelihood consists of two parts: the classical regression for the uncensored observations and the relevant probabilities that an observation is censored (18).
It can be seen that in both datasets a considerable fraction of data is censored across some dimensions (genes), whereas for other dimensions no censoring occurred (i.e. expression of the respective gene could be detected with a Ct number below the LOD for all cells).
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Survival data are censored at one year.
Data were censored at 3-months and are mean (SD) unless otherwise stated.
In the survival analysis, all data were censored at a follow-up after 5 years.
In the survival analysis, data were censored at a follow-up time of 5 years.
In the survival analysis, all data was censored at a follow-up after 5years.
Data were censored at 28 days since the fourth day after admission.
In this paper we present the construction of robust designs for a possibly misspecified generalized linear regression model when the data are censored.
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