EWTPR: Expected win time against trial population With redistribution to the right

Description

Calculates the combined arm state space probabilities using a Markov model or a Kaplan-Meier model (recommended). This function uses these probabilities to compare each participant's clinical state to a distribution of combined arm states. Calculation is extended by redistribution-to-the-right principles

Usage

EWTPR(
  n,
  m,
  nunique2,
  maxfollow2,
  untimes2,
  Time,
  Delta,
  dist2,
  markov_ind,
  cov,
  trt,
  comkm,
  trans_prob2,
  nunique1,
  maxfollow1,
  untimes1,
  dist1,
  trtkm,
  trans_prob1,
  nunique0,
  maxfollow0,
  untimes0,
  dist0,
  conkm,
  trans_prob0,
  nimp
)

Value

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

Arguments

n: The total number of trial participants.
m: The number of events in the hierarchy.
nunique2: The number of unique combined arm event times (returned from wintime::markov() or wintime::km()).
maxfollow2: The max combined arm follow up time (days) (returned from wintime::markov() or wintime::km()).
untimes2: A vector containing unique combined arm 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.
dist2: A matrix of combined arm 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).
comkm: A m x nunique matrix of combined arm survival probabilities (returned from wintime::markov() or wintime::km()).
trans_prob2: A (m x m x number of combined arm event times) matrix where (i,j,k)'th value is transition probability from state i to state j at k'th combined arm event time. (returned from wintime::markov() or wintime::km()).
nunique1: The number of unique trt arm event times (returned from wintime::markov() or wintime::km()).
maxfollow1: The max trt arm follow up time (days) (returned from wintime::markov() or wintime::km()).
untimes1: A vector containing unique trt arm event times (days) (returned from wintime::markov() or wintime::km()).
dist1: A matrix of trt arm state probabilities (returned from wintime::markov() or wintime::km()).
trtkm: A m x nunique matrix of trt arm survival probabilities (returned from wintime::markov() or wintime::km()).
trans_prob1: A (m x m x number of trt arm event times) matrix where (i,j,k)'th value is transition probability from state i to state j at k'th trt arm event time. (returned from wintime::markov() or wintime::km()).
nunique0: The number of unique control arm event times (returned from wintime::markov() or wintime::km()).
maxfollow0: The max control arm follow up time (days) (returned from wintime::markov() or wintime::km()).
untimes0: A vector containing unique control arm event times (days) (returned from wintime::markov() or wintime::km()).
dist0: A matrix of control arm state probabilities (returned from wintime::markov() or wintime::km()).
conkm: A m x nunique matrix of control arm survival probabilities (returned from wintime::markov() or wintime::km()).
trans_prob0: A (m x m x number of control arm event times) matrix where (i,j,k)'th value is transition probability from state i to state j at k'th control arm event time. (returned from wintime::markov() or wintime::km()).
nimp: The number of random imputations.