risk_binary {pseval}

Risk model for binary outcome

Description

Risk model for binary outcome

Usage

risk_binary(model = Y ~ S.1 * Z, D = 5000, risk = risk.logit)

Arguments

model

Formula specifying the risk model

D

number of samples for the simulated annealing integration

risk

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