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pseval: Methods for Evaluating Principal Surrogates of Treatment Response

Installation

pseval is an R package aimed at implementing existing methods for surrogate evaluation using a flexible and common interface. Development will take place on the Github page, and the current version of the package can be installed from CRAN.

install.packages("pseval")

Check out the vignette for methodological details and information on how to use the package.

Check out the cheat sheet for a quick reference.

References

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Version

Install

install.packages('pseval')

Monthly Downloads

171

Version

1.3.3

License

MIT + file LICENSE

Maintainer

Michael Sachs

Last Published

April 8th, 2025

Functions in pseval (1.3.3)

integrate_semiparametric

Semiparametric integration model using the location-scale model
generate_example_data

Generate sample data used for testing
plot.psdesign

Plot summary statistics for a psdesign object
risk_weibull

Weibull risk model for time to event outcome
risk_exponential

Exponential risk model for time to event outcome
summary.psdesign

Summary method for psdesign objects
summarize_bs

Summarize bootstrap samples
risk_poisson

Poisson risk model for count outcomes
wem_test

Test for wide effect modification
verify_trt

Check that a variable is suitable for using as binary treatment indicator
print.psdesign

Concisely print information about a psdesign object
riskcalc

Calculate risks with handlers for survival data
integrate_bivnorm

Bivariate normal integration models for the missing S(1)
risk.probit

Probit link function
risk.logit

Logit link function
integrate_nonparametric

Nonparametric integration model for the missing S(1)
integrate_parametric

Parametric integration model for the missing S(1)
psdesign

Specify a design for a principal surrogate evaluation
pseudo_score

Estimate parameters from a specified model using pseudo-score
risk_binary

Risk model for binary outcome
risk_continuous

Risk model for continuous outcome
sp_locscale

Fit the semi-parametric location-scale model
stg

Compute the standardized total gain
add_bootstrap

Bootstrap resampling parameters
empirical_VE

Compute the empirical Treatment Efficacy
calc_risk

Calculate the risk and functions of the risk
TE

Treatment efficacy contrast functions
add_integration

Integration models
empirical_TE

Compute the empirical Treatment Efficacy
add_estimate

Estimate parameters
add_riskmodel

Add risk model to a psdesign object
calc_STG

Calculate the Standardized total gain
ps_bootstrap

Estimate parameters from a specified model using bootstrap resampling and estimated maximum likelihood
ps_estimate

Estimate parameters from a specified model using estimated maximum likelihood
expand_augdata

Expand augmented data using the integration function
+.ps

Modify a psdesign object by adding on new components.