Bivariate normal integration models for the missing S(1)

This model assumes that the pair [S(1), W] is bivariate normal, where W is the BIP. The means, standard deviations, and correlation are estimated or fixed before calling this function. Then the conditional normal formula is applied in order to get the distribution of S(1) | W. That distribution is used to integrate over the missing S(1) values. This method requires a BIP in the design.

Usage

integrate_bivnorm(x = "S.1", mu = c(0, 0), sd = c(1, 1), rho = 0.2)

Arguments

x,

expression identifying the variable to be integrated. Typically this is S.1 or S.0

mu,

means of the pair of surrogates, missing one first

sd,

standard deviations of the pair, missing one first

rho,

the correlation between X1 and X2