rpact: Confirmatory Adaptive Clinical Trial Design and Analysis


getPiecewiseSurvivalTime {rpact}R Documentation

Get Piecewise Survival Time

Description

Returns a PiecewiseSurvivalTime object that contains the all relevant parameters of an exponential survival time cumulative distribution function. Use names to obtain the field names.

Usage

getPiecewiseSurvivalTime(
  piecewiseSurvivalTime = NA_real_,
  ...,
  lambda1 = NA_real_,
  lambda2 = NA_real_,
  hazardRatio = NA_real_,
  pi1 = NA_real_,
  pi2 = NA_real_,
  median1 = NA_real_,
  median2 = NA_real_,
  eventTime = 12L,
  kappa = 1,
  delayedResponseAllowed = FALSE
)

Arguments

piecewiseSurvivalTime

A vector that specifies the time intervals for the piecewise definition of the exponential survival time cumulative distribution function (see details).

...

Ensures that all arguments (starting from the "...") are to be named and that a warning will be displayed if unknown arguments are passed.

lambda1

The assumed hazard rate in the treatment group, there is no default. lambda1 can also be used to define piecewise exponentially distributed survival times (see details).

lambda2

The assumed hazard rate in the reference group, there is no default. lambda2 can also be used to define piecewise exponentially distributed survival times (see details).

hazardRatio

The vector of hazard ratios under consideration. If the event or hazard rates in both treatment groups are defined, the hazard ratio needs not to be specified as it is calculated, there is no default.

pi1

A numeric value or vector that represents the assumed event rate in the treatment group, default is seq(0.2, 0.5, 0.1) (power calculations and simulations) or seq(0.4, 0.6, 0.1) (sample size calculations).

pi2

A numeric value that represents the assumed event rate in the control group, default is 0.2.

median1

The assumed median survival time in the treatment group, there is no default.

median2

The assumed median survival time in the reference group, there is no default.

eventTime

The assumed time under which the event rates are calculated, default is 12.

kappa

A numeric value >= 0. A kappa != 1 will be used for the specification of the shape of the Weibull distribution. Default is 1, i.e., the exponential survival distribution is used instead of the Weibull distribution. Note that the Weibull distribution cannot be used for the piecewise definition of the survival time distribution, i.e., only lambda and kappa need to be specified. This function is equivalent to pweibull(t, shape = kappa, scale = 1 / lambda) of the stats package, i.e., the scale parameter is 1 / 'hazard rate'.
For example,
getPiecewiseExponentialDistribution(time = 130, piecewiseLambda = 0.01, kappa = 4.2) and pweibull(q = 130, shape = 4.2, scale = 1 / 0.01) provide the sample result.

delayedResponseAllowed

If TRUE, delayed response is allowed; otherwise it will be validated that the response is not delayed, default is FALSE.

Value

Returns a PiecewiseSurvivalTime object. The following generics (R generic functions) are available for this result object:

Staggered patient entry

The first element of the vector piecewiseSurvivalTime must be equal to 0. piecewiseSurvivalTime can also be a list that combines the definition of the time intervals and hazard rates in the reference group. The definition of the survival time in the treatment group is obtained by the specification of the hazard ratio (see examples for details).

How to get help for generic functions

Click on the link of a generic in the list above to go directly to the help documentation of the rpact specific implementation of the generic. Note that you can use the R function methods to get all the methods of a generic and to identify the object specific name of it, e.g., use methods("plot") to get all the methods for the plot generic. There you can find, e.g., plot.AnalysisResults and obtain the specific help documentation linked above by typing ?plot.AnalysisResults.

Examples

getPiecewiseSurvivalTime(lambda2 = 0.5, hazardRatio = 0.8)

getPiecewiseSurvivalTime(lambda2 = 0.5, lambda1 = 0.4)

getPiecewiseSurvivalTime(pi2 = 0.5, hazardRatio = 0.8)

getPiecewiseSurvivalTime(pi2 = 0.5, pi1 = 0.4)

getPiecewiseSurvivalTime(pi1 = 0.3)

getPiecewiseSurvivalTime(hazardRatio = c(0.6, 0.8), lambda2 = 0.4)

getPiecewiseSurvivalTime(piecewiseSurvivalTime = c(0, 6, 9), 
    lambda2 = c(0.025, 0.04, 0.015), hazardRatio = 0.8)

getPiecewiseSurvivalTime(piecewiseSurvivalTime = c(0, 6, 9), 
    lambda2 = c(0.025, 0.04, 0.015), 
    lambda1 = c(0.025, 0.04, 0.015) * 0.8)

pwst <- getPiecewiseSurvivalTime(list(
    "0 - <6"   = 0.025, 
    "6 - <9"   = 0.04, 
    "9 - <15"  = 0.015, 
    "15 - <21" = 0.01, 
    ">=21"     = 0.007), hazardRatio = 0.75)
pwst

# The object created by getPiecewiseSurvivalTime() can be used directly in 
# getSampleSizeSurvival():
getSampleSizeSurvival(piecewiseSurvivalTime = pwst)

# The object created by getPiecewiseSurvivalTime() can be used directly in 
# getPowerSurvival():
getPowerSurvival(piecewiseSurvivalTime = pwst, 
    maxNumberOfEvents = 40, maxNumberOfSubjects = 100)

 

[Package rpact version 3.0.0 Index | www.rpact.org]