adjust.latent {cate} | R Documentation |
Adjust for latent factors, after rotationn
Description
Adjust for latent factors, after rotationn
Usage
adjust.latent(
corr.margin,
n,
X.cov,
Gamma,
Sigma,
method = c("rr", "nc", "lqs"),
psi = psi.huber,
nc = NULL,
nc.var.correction = TRUE
)
Arguments
corr.margin |
marginal correlations, p*d1 matrix |
n |
sample size |
X.cov |
estimated second moment of X, d*d matrix |
Gamma |
estimated confounding effects, p*r matrix |
Sigma |
diagonal of the estimated noise covariance, p*1 vector |
method |
adjustment method |
psi |
derivative of the loss function in robust regression, choices are
|
nc |
position of the negative controls |
nc.var.correction |
correct asymptotic variance based on our formula |
Details
The function essentially runs a regression of corr.margin
~ Gamma
.
The sample size n
is needed to have the right scale.
This function should only be called if you know what you are doing.
Most of the time you want to use the main function cate
to adjust for confounders.
Value
a list of objects
- alpha
estimated alpha, r*d1 matrix
- beta
estimated beta, p*d1 matrix
- beta.cov.row
estimated row covariance of
beta
, a length p vector- beta.cov.col
estimated column covariance of
beta
, a d1*d1 matrix