Specify the columns of the data frame required by score imputation method
col.headings(arm, has.event, time, Id, DCO.time, to.impute, censor.type = NULL)A list contain the given arguments
column name which will contain the subject's treatment group
column name which will contain whether the subject has an event (1) or not(0)
column name of censoring/event time
column name of subject Id
column name of the time at which the subject would have been censored had they not had an event before data cut off
column name of the logical column as to whether events should be imputed
column name of the column containing the reason for censoring, 0=had event, 1=non-administrative censoring 2=administrative censoring -- only subjects with 1 in this column count as having an `event' in the Cox model for censoring (optionally used -- if not used then all subjects who are censored are used)