ten  R Documentation 
time, event(s) and number at risk.
ten(x, ...) ## S3 method for class 'numeric' ten(x, ...) ## S3 method for class 'Surv' ten(x, ..., call = NULL) ## S3 method for class 'coxph' ten(x, ..., abbNames = TRUE, contrasts.arg = NULL) ## S3 method for class 'survfit' ten(x, ..., abbNames = TRUE, contrasts.arg = NULL) ## S3 method for class 'formula' ten(x, ..., abbNames = TRUE, contrasts.arg = NULL) ## S3 method for class 'data.frame' ten(x, ..., abbNames = TRUE, contrasts.arg = NULL, call = NULL) ## S3 method for class 'data.table' ten(x, ..., abbNames = TRUE, mm = NULL, call = NULL) ## S3 method for class 'ten' ten(x, ..., abbNames = NULL, call = NULL)
x 
For the default method, a 
... 
Additional arguments (not implemented). 
call 
Used to pass the 
abbNames 
Abbreviate names?

contrasts.arg 
Methods for handling factors.

mm 
Used to pass the 
A data.table
with the additional class
ten
.
By default, the shape returned is 'long' i.e. there is one row for each unique
timepoint per covariate group.
The basic form, for a numeric
or Surv
object, has columns:
t 
time. 
e 
number of events. 
n 
number at risk. 
A survfit
, coxph
or formula
object
will have additional columns:
cg 
covariate group. This is formed by combining the variables; these are separated by a comma ','. 
ncg 
number at risk, by covariate group 
Special terms.
The following are considered 'special'
terms in a survival model:
strata 
For a stratified model, 
cluster 
These terms are dropped. 
tt 
The variable is unchanged. That is, timetransform
terms are handled as if the the function

Attribures.
The returned object will also have the following attributes
:
shape 
The default is 
abbNames 
Abbreviate names? 
longNames 
A 
ncg 
Number of covariate groups 
call 
The call used to generate the object 
mm 
The 
Additional attributes will be added by the following functions:
sf
ci
The methods for data.frame
(for a model frame)
and data.table
are not typically intended for interactive use.
Currently only binary status and rightcensoring
are supported.
In stratified models, only one level of stratification is supported
(i.e. strata cannot be 'nested' currently).
Partial matching is available for the
following arguments, based on the characters in bold:
abbNames
contrasts.arg
asWide
print
require("survival") ## binary vector ten(c(1, 0, 1, 0, 1)) ## Surv object df0 < data.frame(t=c(1, 1, 2, 3, 5, 8, 13, 21), e=rep(c(0, 1), 4)) s1 < with(df0, Surv(t, e, type="right")) ten(s1) ## some awkward values suppressWarnings( s1 < Surv(time=c(Inf, 1, NaN, NA, 10, 12), event=c(c(NA, 1, 1, NaN, Inf, 0.75)))) ten(s1) ## coxph object ## K&M. Section 1.2. Table 1.1, page 2. data("hodg", package="KMsurv") hodg < data.table::data.table(hodg) data.table::setnames(hodg, c(names(hodg)[!names(hodg) %in% c("score", "wtime")], "Z1", "Z2")) c1 < coxph(Surv(time=time, event=delta) ~ Z1 + Z2, data=hodg[gtype==1 & dtype==1, ]) ten(c1) data("bmt", package="KMsurv") ten(c1 < coxph(Surv(t2, d3) ~ z3*z10, data=bmt)) ## T&G. Section 3.2, pg 47. ## stratified model data("pbc", package="survival") c1 < coxph(Surv(time, status==2) ~ log(bili) + age + strata(edema), data=pbc) ten(c1) ## K&M. Example 7.2, pg 210. data("kidney", package="KMsurv") with(kidney[kidney$type==2, ], ten(Surv(time=time, event=delta))) s1 < survfit(Surv(time=time, event=delta) ~ type, data=kidney) ten(s1)[e > 0, ] ## A null model is passed to ten.Surv (t1 < with(kidney, ten(Surv(time=time, event=delta) ~ 0))) ## but the original call is preserved attr(t1, "call") ## survival::survfit doesn't accept interaction terms... ## Not run: s1 < survfit(Surv(t2, d3) ~ z3*z10, data=bmt) ## End(Not run) ## but ten.formula does: ten(Surv(time=t2, event=d3) ~ z3*z10, data=bmt) ## the same is true for the '.' (dot operator) in formulas (t1 < ten(Surv(time=t2, event=d3) ~ ., data=bmt)) ## impractical long names stored as an attribute attr(t1, "longNames") ## not typically intended to be called directly mf1 < stats::model.frame(Surv(time, status==2) ~ age + strata(edema) + strata(spiders), pbc, drop.unused.levels = TRUE) ten(mf1)
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