autoMAR | R Documentation |
This function will automatically identify the missing patterns and flag the variables if they are not missing at random based on the AUC method
autoMAR( data, aucv = 0.9, strataname = NULL, stratasize = NULL, mar_method = "glm" )
data |
[data.frame | Required] dataframe or data.table |
aucv |
[integer | Optional] auc cut-off value for the not missing at random variable selection |
strataname |
[text | Optional] vector of stratification variables |
stratasize |
[integer | Optional] vector of stratum sample sizes (in the order in which the strata are given in the input dataset). |
mar_method |
[text | Optional] missing at random classification method ("glm", "rf"). Default GLM is used (GLM runs faster for high dimensional data) |
list output including missing variable summary and number of MAR flag variables
# create missing at random features marobj <- autoMAR (heart, aucv = 0.9, strataname = NULL, stratasize = NULL, mar_method = "glm")
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