Perform Univariate Linear Regression Separately for Columns of X
Source:R/univariate_regression.R
univariate_regression.Rd
This function performs the univariate linear
regression y ~ x separately for each column x of X. Each regression
is implemented using .lm.fit()
. The estimated effect size
and stardard error for each variable are outputted.
Usage
univariate_regression(
X,
y,
Z = NULL,
center = TRUE,
scale = FALSE,
return_residuals = FALSE
)
Arguments
- X
n by p matrix of regressors.
- y
n-vector of response variables.
- Z
Optional n by k matrix of covariates to be included in all regresions. If Z is not
NULL
, the linear effects of covariates are removed from y first, and the resulting residuals are used in place of y.- center
If
center = TRUE
, center X, y and Z.- scale
If
scale = TRUE
, scale X, y and Z.- return_residuals
Whether or not to output the residuals if Z is not
NULL
.