Methods for Evaluating Principal Surrogates of Treatment Response
Bivariate normal integration models for the missing S(1)
Nonparametric integration model for the missing S(1)
Parametric integration model for the missing S(1)
Semiparametric integration model using the location-scale model
Fit the semi-parametric location-scale model
Compute the standardized total gain
Summarize bootstrap samples
Summary method for psdesign objects
Treatment efficacy contrast functions
Check that a variable is suitable for using as binary treatment indica...
Test for wide effect modification
Exponential risk model for time to event outcome
Poisson risk model for count outcomes
Weibull risk model for time to event outcome
Logit link function
Probit link function
Calculate risks with handlers for survival data
Risk model for binary outcome
Bootstrap resampling parameters
Estimate parameters
Integration models
Add risk model to a psdesign object
Calculate the risk and functions of the risk
Calculate the Standardized total gain
Compute the empirical Treatment Efficacy
Compute the empirical Treatment Efficacy
Expand augmented data using the integration function
Generate sample data used for testing
Risk model for continuous outcome
Plot summary statistics for a psdesign object
Modify a psdesign object by adding on new components.
Concisely print information about a psdesign object
Estimate parameters from a specified model using bootstrap resampling ...
Estimate parameters from a specified model using estimated maximum lik...
Specify a design for a principal surrogate evaluation
Estimate parameters from a specified model using pseudo-score
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.