risk_binary

model

<p>number of samples for the simulated annealing integration</p>

<p>Function for transforming a linear predictor into a probability.
E.g., risk.logit for the logistic model, risk.probit for the probit model</p>

risk

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.

Michael Sachs

risk_binary: Risk model for binary outcome

Description

Usage

Arguments