augment.flexsurvreg | R Documentation |
Augment accepts a model object and a dataset and adds information about each observation in the dataset. Most commonly, this includes predicted values in the .fitted
column, residuals in the .resid
column, and standard errors for the fitted values in a .se.fit
column. New columns always begin with a . prefix to avoid overwriting columns in the original dataset.
## S3 method for class 'flexsurvreg' augment( x, data = NULL, newdata = NULL, type.predict = "response", type.residuals = "response", ... )
x |
Output from |
data |
A |
newdata |
A |
type.predict |
Character indicating type of prediction to use. Passed to the |
type.residuals |
Character indicating type of residuals to use. Passed to the type argument of |
... |
Additional arguments. Not currently used. |
If neither of data
or newdata
are specified, then model.frame(x)
will be used. It is worth noting that model.frame(x)
will include a Surv
object and not the original time-to-event variables used when fitting the flexsurvreg
object. If the original data is desired, specify data
.
A tibble
containing data
or newdata
and possible additional columns:
.fitted
Fitted values of model
.se.fit
Standard errors of fitted values
.resid
Residuals (not present if newdata
specified)
fit <- flexsurvreg(formula = Surv(futime, fustat) ~ age, data = ovarian, dist = "exp") augment(fit, data = ovarian)
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