summary.ptwiseELtest {survELtest} | R Documentation |
Summary function for ptwiseELtest object
Description
Returns a list with a data frame containing the observed uncensored time points, and the decisions, statistics, and critical values of the pointwise EL tests at those time points.
Usage
## S3 method for class 'ptwiseELtest'
summary(object, digits = max(3L, getOption("digits") - 3L), quiet = FALSE, ...)
Arguments
object |
the result of a call to the |
digits |
significant digits to print, the default value is |
quiet |
a logical indicating whether to reduce the amount of output or not, the default value is |
... |
for future method |
Value
summary.ptwiseELtest
returns a list with following components:
-
call
the statement used to create theptwiseELtest
object -
result_dataframe
a dataframe withtime_pts
in the first column,decision
in the second column,stat_ptwise
in the third column andcritval_ptwise
in the fourth column.-
time_pts
a vector containing the observed uncensored time points at which the Kaplan—Meier estimate is positive and less than1
for each sample. -
decision
a vector containing the decisions of the pointwise EL tests attime_pts
. The decision at each oftime_pts
is1
for rejection of the null hypothesis that the survival functions are the same at the specific time point, and0
otherwise. -
stat_ptwise
a vector containing the pointwise EL statistics attime_pts
. -
critval_ptwise
a vector containing the critical values for pointwise EL testing attime_pts
.
-
See Also
hepatitis
, ptwiseELtest
, print.ptwiseELtest
Examples
library(survELtest)
result = ptwiseELtest(survival::Surv(hepatitis$time, hepatitis$censor)~
hepatitis$group, sided = 1)
summary(result)
## OUTPUT:
## Call:
## ptwiseELtest(formula = survival::Surv(hepatitis$time, hepatitis$censor) ~
## hepatitis$group, sided = 1)
##
## time_pts decision stat_ptwise critval_ptwise
## 1 5.2 0 0.3005 2.951
## 2 9.7 0 0.0000 2.833
## 3 12.9 0 0.1627 2.748
## 4 14.0 0 0.6114 2.583
## 5 14.9 0 2.0010 2.780
## 6 15.7 1 3.7873 2.764
## 7 18.0 1 3.0722 2.652
## 8 18.9 0 1.8878 2.454
## 9 19.2 1 2.5896 2.339
## 10 19.7 0 1.6133 2.601
## 11 20.0 0 2.2393 2.383
## 12 21.7 1 3.6936 2.192
## 13 24.0 1 4.5083 2.300
## 14 24.9 1 5.3743 2.391
## 15 26.0 1 6.2879 2.253
## 16 26.9 1 9.2827 2.117
## 17 27.8 1 10.3581 2.209
## 18 28.0 1 6.9862 2.317
## 19 30.0 1 7.9190 2.346
## 20 31.2 1 6.5074 2.318
## 21 32.1 1 4.9709 2.310
## 22 34.1 1 5.7455 2.360
## 23 36.1 1 6.5627 2.244
## 24 44.9 1 5.4374 2.363
## 25 45.2 1 6.2240 2.416
## 26 47.8 1 7.0519 2.409
## 27 54.1 1 7.9198 2.427
## 28 54.9 1 6.7260 2.310
## 29 58.1 1 7.5667 2.456
## 30 59.8 1 7.2524 2.483
## 31 63.2 1 6.1770 2.511
## 32 70.4 1 5.2110 2.562
## 33 76.1 1 4.3461 2.683
## 34 80.1 1 3.5753 2.744
## 35 81.3 1 2.8926 2.467
## 36 82.1 0 2.2925 2.669
## 37 90.1 1 2.7908 2.543
## 38 92.1 0 2.2120 2.523
## 39 95.0 0 1.7079 2.755
## 40 99.0 0 2.1383 2.762
## 41 108.2 0 2.6206 2.652
## 42 109.9 1 3.1475 2.630
## 43 117.0 0 2.5398 2.646
## 44 148.8 1 3.0555 2.685
## 45 153.1 0 2.4658 2.774