Abstract
Composite endpoints are a popular outcome in controlled studies. However, the required sample size is not easily obtained due to the assortment of outcomes, correlations between them and the way in which the composite is constructed. Data simulations are required. A macro is developed that enables sample size and power estimation.
DOI
10.22237/jmasm/1509495120
Recommended Citation
Brown, P. M., & Ezekowitz, J. A. (2017). Power and Sample Size Estimation for Nonparametric Composite Endpoints: Practical Implementation using Data Simulations. Journal of Modern Applied Statistical Methods, 16(2), 215-230. doi: 10.22237/jmasm/1509495120
simul_data.sas (12 kB)
macro to run simulations
NearestCorr.sas (2 kB)
macro called in simul_data.sas
derive_GR.sas (3 kB)
macro to derive global rank composite
derive_ZS.sas (4 kB)
macro to derive average Z-score composite
derive_WR.sas (4 kB)
macro to derive unmatched win-ratio composite
macro to run simulations
NearestCorr.sas (2 kB)
macro called in simul_data.sas
derive_GR.sas (3 kB)
macro to derive global rank composite
derive_ZS.sas (4 kB)
macro to derive average Z-score composite
derive_WR.sas (4 kB)
macro to derive unmatched win-ratio composite
Included in
Applied Statistics Commons, Social and Behavioral Sciences Commons, Statistical Theory Commons
