integrate_bivnorm

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

means of the pair of surrogates, missing one first

mu, 

standard deviations of the pair, missing one first

sd, 

rho, 

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.

Contains the core methods for the evaluation of principal
surrogates in a single clinical trial. Provides a flexible interface for
defining models for the risk given treatment and the surrogate, the models
for integration over the missing counterfactual surrogate responses, and the
estimation methods. Estimated maximum likelihood and pseudo-score can be used
for estimation, and the bootstrap for inference. A variety of post-estimation
summary methods are provided, including print, summary, plot, and testing.

integrate_bivnorm: Bivariate normal integration models for the missing S(1)

Description

Usage

Arguments