ptc: Prepares and fits a PTC Cox model

Description Usage Arguments Value Author(s) References Examples

View source: R/tccox.r

Description

Calls treatinit() to prepare dataset

Calls addtc() to create TC intervals

Calls ptcfitter() to fit PTC model

Usage

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ptc(dataset, ncov, cov_names, maxfollow, nmaxint, interval_width, min_future_events)

Arguments

dataset

data.frame organized as expected by tc()

ncov

number of baseline covariates (including treatment) to be included in model

cov_names

vector of baseline covariate names (including treatment)

maxfollow

maximum followup for any subject in dataset

nmaxint

maximum number of TC intervals allowed

interval_width

width of the TC intervals

min_future_events

minimum number of events expected of future starters(stoppers) of treatment for determining upper bound on starting(stopping) TC intervals

Value

fit_ptc

fit of PTC model

nstartint

number of TC starting intervals

startint

vector containing the TC starting interval endpoints

nstopint

number of TC stopping intervals

stopint

vector containing the TC stopping interval endpoints

cov_names1

vector containing the covariate names of the model

nperson

number of subjects in dataset

numevents

number of events in dataset

medianfollowup

median followup for subjects in dataset

Author(s)

James F. Troendle

References

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.

Examples

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##---- 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)
{
  }

tccox documentation built on Dec. 3, 2017, 5:04 p.m.

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