ptehd {freebird} | R Documentation |
Proportion of treatment effect explained by high-dimensional surrogates
Description
Estimates the proportion of the treatment effect explained by the indirect effect via high-dimensional surrogates.
Usage
ptehd(Yt, Yc, St, Sc, lambda_range = c(0, 1))
Arguments
Yt |
The n-dmensional outcome vector in the treatment group. |
Yc |
The n-dmensional outcome vector in the control group. |
St |
The n x p matrix of surrogates in the treatment group. |
Sc |
The n x p matrix of surrogates in the treatment group. |
lambda_range |
Min and max of range of range of tuning parameter to use during the constrained l1 optimization step. |
Value
A list with components:
est_id |
Estimate of indirect effect, defined as |
sd_id |
Standard deviation of indirect effect estimate |
est_total |
Estimate of total effect |
sd_total |
Standard deviation of total effect estimate |
V |
Covariance matrix of (est_id, est_total) |
est_R |
Estimate of proportion of treatment effect explained by surrogates |
sd_R |
Standard deviation of proportion estimate |
lambda_used |
lambda used during optimization |
Author(s)
Ruixuan Zhou
Examples
n = 10
St = replicate(n, rnorm(20, mean = 1))
Sc = replicate(n, rnorm(20))
Yt = 1 + rowSums(St) / 2 + rnorm(n)
Yc = rowSums(Sc) / 3 + rnorm(n)
# Requires installation of mosek to run
## Not run:
out = ptehd(Yt, Yc, St, Sc)
## End(Not run)