riskset | R Documentation |
Identify set of individuals at risk of experiencing the event before event time (failure time), t_i. The risk set, R_i, is the set of individuals, j, who had not experienced the event or had been censored by time t_i. This function identifies this set and computes event times satisfying this.
riskset( formula, data, contrasts.arg = NULL, xlevs = NULL, scaleX = TRUE, na.action = na.omit )
formula |
Object of class formula describing
the model. The response and terms are specified
similar to |
data |
optional data frame containing variables specified in the formula. |
contrasts.arg |
an optional list. See
the contrasts.arg of
|
xlevs |
a named list of character vectors
giving the full set of levels to be assumed
for each factor. See |
scaleX |
logical. If TRUE (default), predictors are scaled/standardized. This is used internally. |
na.action |
a function which indicates
what should happen when the data contain NAs.
See |
Let t_1 < t_2 <, ..., t_m, such that m < n if there are not ties, otherwise m = n. If covariates are time-independent the risk set, R_i, is the set of individuals who are still at risk at time t_i, i.e., individuals with event/censoring time y_j≥ t_i. For time-dependent covariates risk set at time t_i is now defined as R(t_i) = \{j : (y^{stop}_{j} ≥ t_i) \wedge (y^{start}_{j} < t_i)\}. The first condition, (y^{stop}_{j} ≥ t_i), ensures that individual j either experienced the event or was censored at a later time point than t_i, while the second condition, (y^{start}_{j} < t_i), ensures the start time was observed before the event.
A list of survival objects:
Y |
Surv object defining the event times and event status. |
X |
model matrix of model terms. |
events |
observed events. |
times |
event times defined by risk set condition. |
timevarlabel, eventvarlabel |
time and event variables, respectively. |
scale_sd, scale_mu |
standard deviation and mean of each of the variable used in standardization. |
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