wintime {wintime} | R Documentation |
Run a win time calculation
Description
This function runs one of the win time methods on observed and resampled data.
Usage
wintime(
type,
Time,
Delta,
trt,
cov = NULL,
model = NULL,
resample = NULL,
resample_num = 0,
time_restriction = NA,
seed = NA,
nimp = 0
)
Arguments
type |
A string value indicating the desired win time method. Methods include 'ewt', 'ewtr', 'rmt', 'max', 'wtr', 'rwtr', 'pwt', 'ewtp', 'rewtp', 'ewtpr','rewtpr', and 'rpwt'. |
Time |
A |
Delta |
A |
trt |
A numeric vector containing treatment arm indicators (1 for treatment, 0 for control). |
cov |
Optional. A |
model |
Optional. String value. The type of model used to calculate state distributions. Options include 'km' and 'markov'. Default depends on |
resample |
Optional. String value. The resampling method run after the observed data calculation. Options include 'boot' and 'perm'. Default depends on |
resample_num |
Optional. The number of desired resamples. Default is 0. |
time_restriction |
Required only for |
seed |
Optional. Seed used for random number generation in resampling. |
nimp |
Required only for |
Details
The type parameter specifies the procedure you would like to run. 'ewt' is Expected Win Time. 'ewtr' is Expected Win Time Against Reference (Control Arm). 'rmt' is Restricted Mean Time in Favor of Treatment. 'max' is the MAX procedure (max(COMP,EWTR)). 'wtr' is Win Time Ratio. 'rwtr' is Restricted Win Time Ratio. 'pwt' is Pairwise Win Time. 'ewtp' is Expected Win Time Against Trial Population. 'ewtpr' is Expected Win Time Against Trial Population With Redistribution. 'rewtp' is Time Restricted Expected Win Time Against Trial Population. 'rewtpr'is Time Restricted Expected Win Time Against Trial Population With Redistribution. 'rpwt' is Time Restricted Pairwise Win Time.
Value
A list containing: the observed treatment effect, a vector of length resample_num
containing resampled treatment effects, a message
indicating the method ran and the type of resampling done, the variance, the p-value, the total wins on treatment (pairwise methods only),
the total losses on treatment (pairwise methods only), a vector of length 'm' with the components of the treatment effect,
a vector of length 'm' with the variance of the components. A warning message will be printed for combinations of type
and model
/resample
that are not recommended.
Examples
# ------------------------------
# Example Inputs
# ------------------------------
# Event time vectors
TIME_1 <- c(256,44,29,186,29,80,11,380,102,33)
TIME_2 <- c(128,44,95,186,69,66,153,380,117,33)
TIME_3 <- c(435,44,95,186,69,270,1063,380,117,33)
# Event time matrix
Time <- rbind(TIME_1, TIME_2, TIME_3)
# Event indicator vectors
DELTA_1 <- c(1,0,1,0,1,1,1,0,1,0)
DELTA_2 <- c(1,0,0,0,0,1,1,0,0,0)
DELTA_3 <- c(0,0,0,0,0,0,0,0,0,0)
# Event indicator matrix
Delta <- rbind(DELTA_1, DELTA_2, DELTA_3)
# Treatment arm indicator vector
trt <- c(1,1,1,1,1,0,0,0,0,0)
# Covariate vectors
cov1 <- c(54,53,55,61,73,65,63,63,82,58,66,66)
cov2 <- c(34.4,32.1,34.7,54.1,55.7,43.6,32.1,44.8,85.2,12.5,33.4,21.4)
# Covariate vectors
cov1 <- c(66,67,54,68,77,65,55,66,77,54)
cov2 <- c(3,6,4,2,3,5,8,5,3,5)
cov3 <- c(34.6,543.6,45.8,54.7,44.3,55.6,65.9,54.7,77.9,31.2)
# Covariate matrix
cov <- cbind(cov1, cov2, cov3)
# ------------------------
# wintime Examples
# ------------------------
# Run WTR
z <- wintime("wtr", Time, Delta, trt)
print(z)
# Run EWT with default settings and 10 resamples
z <- wintime("ewt", Time, Delta, trt, resample_num = 10)
print(z)
# Run EWTR with default settings
z <- wintime("ewtr", Time, Delta, trt, cov = cov)
print(z)
# Run EWTR with KM model (This will produce a warning message)
z <- wintime("ewtr", Time, Delta, trt, cov = cov, model = "km")
print(z)