impute_conditional_mean: Impute missing values by their conditional mean
In metamisc: Meta-Analysis of Diagnosis and Prognosis Research Studies

Description Usage Arguments Value Author(s) Examples

This function imputes missing values by their conditional mean

1	impute_conditional_mean(x, mu, Sigma)

`x`	A vector with observations, some of which may be missing (indicated by NA)
`mu`	A vector with the population means for 'x'. No missing values are allowed here.
`Sigma`	A matrix describing the population covariance of 'x'

A vector where missing values for 'x' have been replaced by their conditional mean

Thomas Debray <thomas.debray@gmail.com>

# Define the population means
mu <- c(0, 1, 2)

# Define the covariance of the population
Sigma <- diag(1,3)
Sigma[1,2] <- Sigma[2,1] <- 0.3 
Sigma[2,3] <- Sigma[3,2] <- 0.1
Sigma[1,3] <- Sigma[3,1] <- -0.2

# Generate a 'random' sample from the population that is partially observed
x <- c(NA, 2, 4)

# Impute the missing values
impute_conditional_mean (x=x, mu=mu, Sigma=Sigma)