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