EWTR: Expected win time against reference

In wintime: Win Time Methods for Time-to-Event Data in Clinical Trials

Expected win time against reference

Description

Calculates the control group state space probabilities using a Markov model (recommended) or a Kaplan-Meier model. This function uses these probabilities to compare each participant's clinical state to a distribution of control group states.

Usage

EWTR(
  n,
  m,
  nunique,
  maxfollow,
  untimes,
  Time,
  Delta,
  dist,
  markov_ind,
  cov,
  trt
)

Arguments

n	The total number of trial participants.
m	The number of events in the hierarchy.
nunique	The number of unique control group event times (returned from wintime::markov() or wintime::km()).
maxfollow	The max control group follow up time (days) (returned from wintime::markov() or wintime::km()).
untimes	A vector containing unique control group event times (days) (returned from wintime::markov() or wintime::km()).
Time	A m x n matrix of event times (days). Rows should represent events and columns should represent participants. Rows should be in increasing order of clinical severity.
Delta	A m x n matrix of event indicators Rows should represent events and columns should represent participants. Rows should be in increasing order of clinical severity.
dist	A matrix of control group state probabilities (returned from wintime::markov() or wintime::km()).
markov_ind	An indicator of the model type used (1 for Markov, 0 for Kaplan-Meier).
cov	A n x p matrix of covariate values, where p is the number of covariates.
trt	A vector of length n containing treatment arm indicators (1 for treatment, 0 for control).

Value

A list containing: The estimated treatment effect from the linear regression model, the variance, and the Z-statistic.

wintime documentation built on Oct. 31, 2024, 5:10 p.m.