sensitivity {BuyseTest}  R Documentation 
Sensitivity Analysis for the Choice of the Thresholds
Description
Evaluate a summary statistic (net benefit, win ratio, ...) using GPC along various thresholds of clinical relevance.
Usage
sensitivity(object, ...)
## S4 method for signature 'S4BuyseTest'
sensitivity(
object,
threshold,
statistic = NULL,
band = FALSE,
conf.level = NULL,
null = NULL,
transformation = NULL,
alternative = NULL,
adj.p.value = FALSE,
trace = TRUE,
cpus = 1,
...
)
Arguments
object 
an R object of class 
... 
argument passsed to the function 
threshold 
[list] a list containing for each endpoint the thresholds to be considered. 
statistic 
[character] the statistic summarizing the pairwise comparison:

band 
[logical] should simulateneous confidence intervals be computed? 
conf.level 
[numeric] confidence level for the confidence intervals.
Default value read from 
null 
[numeric] right hand side of the null hypothesis (used for the computation of the pvalue). 
transformation 
[logical] should the CI be computed on the logit scale / log scale for the net benefit / win ratio and backtransformed.
Otherwise they are computed without any transformation.
Default value read from 
alternative 
[character] the type of alternative hypothesis: 
adj.p.value 
[logical] should pvalue adjusted for multiple comparisons be computed? 
trace 
[logical] Should the execution of the function be traced? 
cpus 
[integer, >0] the number of CPU to use. Default value is 1. 
Details
Simulateneous confidence intervals and adjusted pvalues are computed using a singlestep maxtest approach via the function transformCIBP
of the riskRegression package.
Value
An S3 object of class S3sensitivity
.
Examples
## Not run:
require(ggplot2)
## simulate data
set.seed(10)
df.data < simBuyseTest(1e2, n.strata = 2)
## with one endpoint
ff1 < treatment ~ TTE(eventtime, status = status, threshold = 0.1)
BT1 < BuyseTest(ff1, data= df.data)
se.BT1 < sensitivity(BT1, threshold = seq(0,2,0.25), band = TRUE)
plot(se.BT1)
## with two endpoints
ff2 < update(ff1, .~. + cont(score, threshold = 1))
BT2 < BuyseTest(ff2, data= df.data)
se.BT2 < sensitivity(BT2, threshold = list(eventtime = seq(0,2,0.25), score = 0:2),
band = TRUE)
plot(se.BT2)
plot(se.BT2, col = NA)
## End(Not run)