ImputeStat {InformativeCensoring}

S3 generic to fit model(s) to risk score/gamma Imputed objects

Description

S3 generic to fit model(s) to risk score/gamma Imputed objects

Usage

## S3 method for class 'GammaImputedData'
ImputeStat(
  object,
  method = c("Cox", "weibull", "exponential")[1],
  formula = NULL,
  ...
)

## S3 method for class 'GammaImputedSet'
ImputeStat(
  object,
  method = c("Cox", "weibull", "exponential")[1],
  formula = NULL,
  ...,
  parallel = c("no", "multicore", "snow")[1],
  ncpus = 1L,
  cl = NULL
)

ImputeStat(
  object,
  method = c("logrank", "Wilcoxon", "Cox", "weibull", "exponential")[1],
  formula,
  ...
)

## S3 method for class 'ScoreImputedSet'
ImputeStat(
  object,
  method = c("logrank", "Wilcoxon", "Cox")[1],
  formula = NULL,
  ...,
  parallel = c("no", "multicore", "snow")[1],
  ncpus = 1L,
  cl = NULL
)

Arguments

object

A ScoreImputedData, ScoreImputedSet, GammaImputedData or GammaImputedSet object to fit the model to

method

The type of statistical model to fit. There are three methods which can be performed when using Risk Score imputation
"logrank": a logrank test using survival::survdiff
"Wilcoxon": Peto & Peto modification of the Gehan-Wilcoxon test using survival::survdiff with rho=1
"Cox": Fit a cox model using survival::coxph

For gamma imputation the model can be "Cox" (using survival::coxph), "weibull" or "exponential" both using survival::coxph

formula

The model formula to fit. If no formula argument is used, then object$default.formula will be used. For risk score imputation this is ~ treatment.group and for gamma imputation this is the formula used when fitting the Cox model

For method="Cox", additional covariates can be included by explictily giving a formula argument. For logrank/Wilcoxon only additional strata terms can be included.

In all cases only the right hand side of the formula is required The survival object on the left hand side is created automatically E.g. for a Cox model could use formula=~arm + covar1. The cluster and tt options cannot be used See the vignettes for further details

...

Additional arguments which are passed into the model fit function

parallel

The type of parallel operation to be used (if any), can be used for GammaImputedSet and ScoreImputedSet

ncpus

integer: number of processes to be used in parallel operation: typically one would chose this to be the number of available CPUs, can be used for GammaImputedSet and ScoreImputedSet.

cl

An optional parallel or snow cluster for use if parallel="snow". If not supplied, a cluster on the local machine is created for the duration of the call, can be used for GammaImputedSet and ScoreImputedSet.

See Also

ScoreStat.object ScoreImputedData.object