Description Usage Arguments Details Value
View source: R/COVIMPUTEFUNCTION_Example.R
The function COVIMPUTEFUNCTION creates a single imputed version of the covariate matrix. An example function is included in the package, but the user must specify their own function when applying MultiCure to datasets with covariate missingness. This function must have input/output as described below.
1  COVIMPUTEFUNCTION(datWIDE, param, ImputeDat, TransCov)

datWIDE 
defined as in MultiCure 
param 
If baselines are WEIBULL, this is a vector containing beta, alpha, scale, and shape. If baselines are COX, this is a vector containing beta and alpha. 
ImputeDat 
This is a list with the following elements:

TransCov 
defined as in MultiCure 
The example code included in the package imputes missing covariate X2 in the Multistate cure model example. In the example code, a normal covariate is imputed using an approach similar to SMCFCS in Bartlett et al. (2014) and MetropolisHastings methods. In practice, this function can use any imputation method the user desires. For example, the userwritten function can call 'mice' in R to perform the imputation.
CovImp a matrix with a SINGLE imputation of the covariate matrix
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