Description Usage Arguments See Also

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

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ```
## 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)
``` |

`object` |
A |

`method` |
The type of statistical model to fit. There are three methods which can be performed when using
Risk Score imputation For gamma imputation the model can be "Cox" (using |

`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 For 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 |

`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 |

`cl` |
An optional parallel or snow cluster for use if |

`ScoreStat.object`

`ScoreImputedData.object`

InformativeCensoring documentation built on May 29, 2017, 7:10 p.m.

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