itcadd: Determines potential ITC intervals according to expected...
In trooper197/tccox: Treatment Choice Cox Model

Description Usage Arguments Value Author(s) References Examples

Either speciifies the ITC interval endpoints as fixed or else determines candidates based on expected event criteria

1 2	itcadd(dataset, nmaxint, interval_width, min_exp_events, nitc_fixed, n_start_fixed, n_stop_fixed, interval_stop_beginning)

`dataset`	data.frame organized as expected by tc()
`nmaxint`	maximum number of TC intervals allowed
`interval_width`	width of the TC intervals
`min_exp_events`	minimum number of events expected of subjects in each cell for determining ITC intervals
`nitc_fixed`	indicator that potential ITC intervals are fixed
`n_start_fixed`	number of fixed ITC starting intervals (only applicable if nitc_fixed=1)
`n_stop_fixed`	number of fixed ITC stopping intervals (only applicable if nitc_fixed=1)
`interval_stop_beginning`	smallest ITC stopping interval endpoint (only applicable if nitc_fixed=1)

`nitc_start`	number of ITC starting intervals
`itc_start_endpoint`	vector containing the ITC starting interval endpoints
`nitc_stop`	number of ITC stopping intervals
`itc_stop_endpoint`	vector containing the ITC stopping interval endpoints

James F. Troendle

Troendle, JF, Leifer, E, Zhang Z, Yang, S, and Tewes H (2017) How to Control for Unmeasured Confounding in an Observational Time-To-Event Study With Exposure Incidence Information: the Treatment Choice Cox Model. Statistics in Medicine 36: 3654-3669.

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (x)
{
  }