hce: Design and Analysis of Hierarchical Composite Endpoints

Simulate and analyze hierarchical composite endpoints. Win odds, also called Wilcoxon-Mann-Whitney or success odds, is the main analysis method. Other win statistics (win probability, win ratio, net benefit) are also implemented in the univariate case, provided there is no censoring. The win probability analysis is based on the Brunner-Munzel test and uses the DeLong-DeLong-Clarke-Pearson variance estimator, as described by Brunner and Konietschke (2025) in “An unbiased rank-based estimator of the Mann–Whitney variance including the case of ties” (Statistical Papers 66 (1): 20, <doi:10.1007/s00362-024-01635-0>). Stratification and covariate adjustment are performed based on the methodology presented by Koch GG et al. in “Issues for covariance analysis of dichotomous and ordered categorical data from randomized clinical trials and non-parametric strategies for addressing them” (Statistics in Medicine 17 (15-16): 1863–92). For a review, see Gasparyan SB et al (2021) “Adjusted win ratio with stratification: Calculation methods and interpretation” (Statistical Methods in Medical Research 30 (2): 580–611, <doi:10.1177/0962280220942558>).

Package details

AuthorSamvel B. Gasparyan [aut, cre] (ORCID: <https://orcid.org/0000-0002-4797-2208>)
MaintainerSamvel B. Gasparyan <gasparyan.co@gmail.com>
LicenseMIT + file LICENSE
Version0.7.2
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("hce")

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hce documentation built on June 8, 2025, 11:43 a.m.