risk_binary: Risk model for binary outcome
In sachsmc/pseval: Methods for Evaluating Principal Surrogates of Treatment Response
Description
Risk model for binary outcome
Usage
1
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
sachsmc/pseval documentation built on May 29, 2019, 12:55 p.m.
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Description
Risk model for binary outcome
Usage
1 | 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 |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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