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adaptDiag

The goal of adaptDiag is to simplify the process of designing adaptive trials for diagnostic test studies. With accumulating data in a clinical trial of a new diagnostic test compared to a gold-standard reference, decisions can be made at interim analyses to either stop the trial for early success, stop the trial for expected futility, or continue to the next sample size look. Designs can be focused around test sensitivity, specificity, or both. The package is heavily influenced by the seminal article by Broglio et al. (2014).

References

Broglio KR, Connor JT, Berry SM. Not too big, not too small: a Goldilocks approach to sample size selection. Journal of Biopharmaceutical Statistics, 2014; 24(3): 685–705.

Installation

You can install the development version of adaptDiag GitHub with:

# install.packages("devtools")
devtools::install_github("graemeleehickey/adaptDiag")

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Install

install.packages('adaptDiag')

Monthly Downloads

313

Version

0.1.0

License

GPL-3

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Maintainer

Hickey Graeme L.

Last Published

August 17th, 2021

Functions in adaptDiag (0.1.0)

summarise_trials

Summarise results of multiple simulated trials to give the operating characteristics
binom_sample_size

Calculate the minimum number of samples required for a one-sided exact binomial test
multi_trial

Simulate and analyse multiple trials