adjust.latent: Adjust for latent factors, after rotationn

In cate: High Dimensional Factor Analysis and Confounder Adjusted Testing and Estimation

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 psi.huber, psi.bisquareand psi.hampel
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

See Also

cate

cate documentation built on July 2, 2020, 4:08 a.m.