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, the Z-statistic, the components of the treatment effect, and the variance of the components.
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).