Description Usage Arguments Details Value See Also Examples

View source: R/gammaImputeData.R

This function performs the Imputation described in Relaxing the independent censoring assumptions in the Cox proportional hazards model using multiple imputation. (2014) D. Jackson et al. Statist. Med. (33) 4681-4694

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`formula` |
The model formula to be used when fitting the models to calculate
the cumulative hazard. A formula for coxph can include strata terms but not
cluster or tt and only right-censored |

`data` |
A time to event data set for which event times are to be imputed |

`m` |
The number of imputations to be created |

`gamma` |
Either column name containing the value of gamma or a vector of values giving the subject specific
size of the step change in the log hazard at censoring. If a subject has NA in this column then no imputation is performed
for this subject (i.e. the subject's censored time remains unchanged after imputation). If a subject has already had an
event then the value of gamma is ignored. If |

`gamma.factor` |
If used, a single numeric value. If no |

`bootstrap.strata` |
The strata argument for stratified bootstrap sampling, see argument |

`DCO.time` |
Either column name containing the subject's data cutoff time or a vector of DCO.times for the subjects or a single number to be used as the DCO.time for all subjects (if imputed events are > this DCO.time then subjects are censored at DCO.time in imputed data sets) |

`...` |
Additional parameters to be passed into the model fit function |

`parallel` |
The type of parallel operation to be used (if any). |

`ncpus` |
integer: number of processes to be used in parallel operation: typically one would chose this to be the number of available CPUs |

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

See the Gamma Imputation vignette for further details

A `GammaImputedSet.object`

containing the imputed data sets

`GammaImputedSet.object`

`GammaImputedData.object`

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## Not run:
data(nwtco)
nwtco <- nwtco[1:500,]
#creating 2 imputed data sets (m=2) for speed, would normally create more
ans <- gammaImpute(formula=Surv(edrel,rel)~histol + instit,
data = nwtco, m=2, gamma.factor=1, DCO.time=6209)
#subject specific gamma (multiplied by gamma.factor to give the jump)
#NA for subjects that are not to be imputed
jumps <- c(rep(NA,10),rep(1,490))
DCO.values <- rep(6209,500)
ans.2 <- gammaImpute(formula=Surv(edrel,rel)~histol + instit + strata(stage),
data = nwtco, m=2, bootstrap.strata=strata(nwtco$stage),
gamma=jumps, gamma.factor=1, DCO.time=DCO.values)
#can also use column names
nwtco$gamma <- jumps
nwtco$DCO.time <- DCO.values
ans.3 <- gammaImpute(formula=Surv(edrel,rel)~histol + instit + strata(stage),
data = nwtco, m=2, bootstrap.strata=strata(nwtco$stage),
gamma="gamma", DCO.time="DCO.time")
## End(Not run)
``` |

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