Learn R Programming

eselect (version 1.1)

Adaptive Clinical Trial Designs with Endpoint Selection and Sample Size Reassessment

Description

Endpoint selection and sample size reassessment for multiple binary endpoints based on blinded and/or unblinded data. Trial design that allows an adaptive modification of the primary endpoint based on blinded information obtained at an interim analysis. The decision rule chooses the endpoint with the lower estimated required sample size. Additionally, the sample size is reassessed using the estimated event probabilities and correlation between endpoints. The implemented design is proposed in Bofill Roig, M., Gómez Melis, G., Posch, M., and Koenig, F. (2022). .

Copy Link

Version

Install

install.packages('eselect')

Monthly Downloads

160

Version

1.1

License

MIT + file LICENSE

Maintainer

Marta Roig

Last Published

February 3rd, 2023

Functions in eselect (1.1)

test_f

test_f
samplesize_OR

samplesize_OR
estimation_b

Blinded estimation of the correlation
eselectsim

Simulation trials with endpoint selection and sample size reassessment for composite endpoints based on blinded data
eselectsim_ub

Simulation trials with endpoint selection and sample size reassessment for composite endpoints based on unblinded data
eselect_ub

Endpoint selection and sample size reassessment for composite endpoints based on unblinded data
eselect

Endpoint selection and sample size reassessment for composite endpoints based on blinded data
test_me

test_me
OR_function

OR_function
estimation_ub

Unblinded estimation of the correlation
corr_rest_b

corr_rest
f_sim

Simulation 2x2 table binary endpoints
f_OR

f_OR
fun_p0

fun_p0
corr_rest_ub

corr_rest_ub: computes the correlation restrictions unblinded case