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