survMisc (version 0.5.4)

# predict: predicted events

predicted events

## Usage

# S3 method for ten
predict(object, ..., eMP = TRUE, reCalc = FALSE)

## Arguments

object

An object of class ten.

eMP

Add column(s) indicating events minus predicted.

...

reCalc

Recalcuate the values? If reCalc=FALSE (the default) and the ten object already has the calculated values stored as an attribute, the value of the attribute is returned directly.

## Value

An attribute, pred is added to object:

t

Times with at least one observation

P_

predicted number of events

And if eMP==TRUE (the default):
eMP_

events minus predicted

The names of the object's covariate groups are used to make the suffixes of the column names (i.e. after the _ character).

## Details

With $$K$$ covariate groups, We use $$ncg_{ik}$$, the number at risk for group $$k$$, to calculate the number of expected events: $$P_{ik} = \frac{e_i(ncg_{ik})}{n_i} \quad k=1, 2 \ldots K$$

?survival::predict.coxph methods("predict")

## Examples

Run this code
# NOT RUN {
## K&M. Example 7.2, Table 7.2, pp 209-210.
data("kidney", package="KMsurv")
k1 <- ten(Surv(time=time, event=delta) ~ type, data=kidney)
predict(k1)
predict(asWide(k1))
stopifnot(predict(asWide(k1))[, sum(eMP_1 + eMP_2)] <=
.Machine\$double.neg.eps)
## Three covariate groups
## K&M. Example 7.4, pp 212-214.
data("bmt", package="KMsurv")
b1 <- ten(Surv(time=t2, event=d3) ~ group, data=bmt)
predict(b1)
## one group only
predict(ten(Surv(time=t2, event=d3) ~ 1, data=bmt))
# }


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