SurrogateRegression (version 0.5.0)

Fit.BNLS: Fit Bivariate Normal Regression Model via Least Squares

Description

Estimation procedure for bivariate normal regression models in which only the target outcome is subject to missingness.

Usage

Fit.BNLS(t, s, X, sig = 0.05)

Value

An object of class 'bnr' with slots containing the estimated regression coefficients, the target-surrogate covariance matrix, the information matrices for the regression and covariance parameters, and the residuals.

Arguments

t

Target outcome vector.

s

Surrogate outcome vector.

X

Model matrix.

sig

Type I error level.

Details

The model matrix is expected in numeric format. Include an intercept if required. Expand factors and interactions in advance.

Examples

# \donttest{
set.seed(100)
n <- 1e3
X <- rnorm(n)
data <- rBNR(X = X, Z = X, b = 1, a = -1, t_miss = 0.1, s_miss = 0.0)
t <- data[, 1]
s <- data[, 2]

# Model fit.
fit_bnls <- Fit.BNLS(
  t = t,
  s = s,
  X = X,
  sig = 0.05
)
# }