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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 as shown below. First you must install the devtools package, if you haven't already install.packages("devtools").

devtools::install_github("sachsmc/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

185

Version

1.3.1

License

MIT + file LICENSE

Maintainer

Michael Sachs

Last Published

January 28th, 2019

Functions in pseval (1.3.1)

calc_risk

Calculate the risk and functions of the risk
empirical_VE

Compute the empirical Treatment Efficacy
add_estimate

Estimate parameters
add_integration

Integration models
empirical_TE

Compute the empirical Treatment Efficacy
risk_binary

Risk model for binary outcome
TE

Treatment efficacy contrast functions
+.ps

Modify a psdesign object by adding on new components.
risk_continuous

Risk model for continuous outcome
expand_augdata

Expand augmented data using the integration function
print.psdesign

Concisely print information about a psdesign object
integrate_nonparametric

Nonparametric integration model for the missing S(1)
add_bootstrap

Bootstrap resampling parameters
integrate_parametric

Parametric integration model for the missing S(1)
add_riskmodel

Add risk model to a psdesign object
risk_exponential

Exponential risk model for time to event outcome
risk_weibull

Weibull risk model for time to event outcome
risk_poisson

Poisson risk model for count outcomes
integrate_semiparametric

Semiparametric integration model using the location-scale model
riskcalc

Calculate risks with handlers for survival data
plot.psdesign

Plot summary statistics for a psdesign object
verify_trt

Check that a variable is suitable for using as binary treatment indicator
sp_locscale

Fit the semi-parametric location-scale model
stg

Compute the standardized total gain
calc_STG

Calculate the Standardized total gain
generate_example_data

Generate sample data used for testing
integrate_bivnorm

Bivariate normal integration models for the missing S(1)
summarize_bs

Summarize bootstrap samples
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
psdesign

Specify a design for a principal surrogate evaluation
summary.psdesign

Summary method for psdesign objects
wem_test

Test for wide effect modification
pseudo_score

Estimate parameters from a specified model using pseudo-score
risk.logit

Logit link function
risk.probit

Probit link function