total number of subjects in each curve.

the time points at which the curve has a step.

the number of subjects at risk at t.

the number of events that occur at time t.

for counting process data only, the number of subjects that enter at time t.

for counting process data only, the number of subjects who exit the risk set, without an event, at time t. (For right censored data, this number can be computed from the successive values of the number at risk).

the estimate of survival at time t+0. This may be a vector or a matrix. The latter occurs when a set of survival curves is created from a single Cox model, in which case there is one column for each covariate set.

a multi-state survival will have the prev component instead of surv. It will be a matrix containing the estimated probability of each state at each time, one column per state. The p0 matrix contains the initial distribution of states. (On further reflection pstate= "probability in state" would have been a much better label than "prevalence", but by that point too many other packages were dependent on the form of the result.)

for a survival curve this contains standard error of the cumulative hazard or -log(survival), for a multi-state curve it contains the standard error of prev. This difference is a reflection of the fact that each is the natural calculation for that case.

optional. For a multi-state curve this is an k by k array for each time point, where k is the number of states.

upper confidence limit for the survival curve or probability

lower confidence limit for the survival curve or probability

if there are multiple curves, this component gives the number of elements of the time etc. vectors corresponding to the first curve, the second curve, and so on. The names of the elements are labels for the curves.

the value specified for the start.time argument, if it was used in the call.

for counting process data, and any time that the start.time argument was used, this contains the total number of observations that were available. Not all may have been used in creating the curve, in which case this value will be larger than n above.

the approximation used to compute the confidence limits.

the level of the confidence limits, e.g. 90 or 95%.

for multi-state data, the total number of transitions of each type.

the returned value from the na.action function, if any. It will be used in the printout of the curve, e.g., the number of observations deleted due to missing values.

an image of the call that produced the object.

type of survival censoring.

optional, for survfitms objects only. A list with one element per stratum, each element of the list is an array indexed by subject, time, state. The time dimension will have one more element than the prev matrix, the first row is the subject's influence on the initial prevalence (just before the first time point). If there is only one curve a list is not needed.