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How do you address informative censoring?
Several methods have been described to deal with the problem of informative censoring. These include imputation techniques for missing data, sensitivity analyses to mimic best and worst-case scenarios and use of the drop-out event as a study end-point.
What is a censoring time?
Censoring is an endemic feature of time-to-event analysis that precludes observation of the event. Right-censoring occurs when an event may have occurred after the last time a person was under observation, but the specific timing of the event is unknown.
What is the key assumption about censoring when analyzing censored survival data?
The main assumption in analyzing TTE data is that of non-informative censoring: individuals that are censored have the same probability of experiencing a subsequent event as individuals that remain in the study. Informative censoring is analogous to non-ignorable missing data, which will bias the analysis.
What is a censoring variable?
In statistics, censoring is a condition in which the value of a measurement or observation is only partially known. The problem of censored data, in which the observed value of some variable is partially known, is related to the problem of missing data, where the observed value of some variable is unknown.
Are there any methods that allow interval censored data?
Presently, the only methods allowing interval censored data are the parametric models computed by survreg and survival curves computed by survfit; for both of these, the distinction between open and closed intervals is unimportant. The distinction is important for counting process data and the Cox model.
What are the options for the status indicator?
The status indicator, normally 0=alive, 1=dead. Other choices are TRUE / FALSE ( TRUE = death) or 1/2 (2=death). For interval censored data, the status indicator is 0=right censored, 1=event at time, 2=left censored, 3=interval censored.
What are the attributes of a Surv object?
Surv objects are implemented as a matrix of 2 or 3 columns that has further attributes. These include the type (left censored, right censored, counting process, etc.) and labels for the states for multi-state objects.