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etsi (version 1.0)

Efficient Testing Using Surrogate Information

Description

Provides functions for treatment effect estimation, hypothesis testing, and future study design for settings where the surrogate is used in place of the primary outcome for individuals for whom the surrogate is valid, and the primary outcome is purposefully measured in the remaining patients. More details are available in: Knowlton, R., Parast, L. (2024) ``Efficient Testing Using Surrogate Information," Biometrical Journal, 67(6): e70086, . A tutorial for this package can be found at .

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Version

Install

install.packages('etsi')

Monthly Downloads

118

Version

1.0

License

GPL

Maintainer

Layla Parast

Last Published

November 6th, 2025

Functions in etsi (1.0)

exampledataB

Example Data (Study B)
exampledataA

Example Data (Study A)
extrapolate.na

Function for extrapolating NA values from kernel smoothing
etsi.main

Estimates the pooled treatment effect quantity, standard error, and corresponding p-value.
etsi.design

Calculates the estimated power for a future Study B or the required sample size to achieve a desired level of power.
check.strong.surr

Calculates whether each individual has a strong surrogate, based on PTE results from Study A and a desired threshold.
get.mu.hat.0

Calculates the conditional expectation of the primary outcome from the control group in Study A, given the surrogate outcome, using kernel smoothing.
calculate.se

Estimates the standard error of the pooled treatment effect quantity.