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CompAREdesign (version 2.3.1)

Statistical Functions for the Design of Studies with Composite Endpoints

Description

It has been designed to calculate the required sample size in randomized clinical trials with composite endpoints. It also calculates the expected effect and the probability of observing the composite endpoint, among others. The methodology can be found in Bofill & Gómez (2019) and Gómez & Lagakos (2013) .

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Version

Install

install.packages('CompAREdesign')

Monthly Downloads

287

Version

2.3.1

License

GPL-3

Maintainer

Marta Roig

Last Published

February 15th, 2024

Functions in CompAREdesign (2.3.1)

Plot graphics related to the composite endpoint.

Gumbel's copula

freedman_formula

Freedman's formula

Effect for composite time-to-event endpoints

schoenfeld_formula

Schoenfeld's formula

Sample size for composite binary endpoints

Lower bound for Pearson's Correlation

Simulation of composite time-to-event endpoints

Survival function for composite time-to-event endpoints

Upper bound for Pearson's Correlation

Sample size for composite time to event endpoints

Simulation of binary composite endpoints

ARE method for composite binary endpoints

ARE method for composite time to event endpoints

Sstar_func_perc

Difference between survival function and a given percentile

Survival function for composite endpoint

Probability of observing the event

Effect for composite binary endpoints

Probability of composite binary endpoints

CompAREdesign-package

CompAREdesign: Statistical Functions for the Design of Studies with Composite Endpoints

MarginalsSelection

Marginal distributions for both components

CopulaSelection

Clayton's copula

Simulation 1-arm