Implementing seven Covariate-Adaptive Randomization to assign patients to two treatments. Three of these procedures can also accommodate quantitative and mixed covariates. Given a set of covariates, the user can generate a single sequence of allocations or replicate the design multiple times by simulating the patients' covariate profiles. At the end, an extensive assessment of the performance of the randomization procedures is provided, calculating several imbalance measures. See Baldi Antognini A, Frieri R, Zagoraiou M and Novelli M (2022) for details.

Rosamarie Frieri, Marco Novelli (2023). R package "covadap".

R package "covadap"

Rosamarie Frieri
;
Marco Novelli
2023

Abstract

Implementing seven Covariate-Adaptive Randomization to assign patients to two treatments. Three of these procedures can also accommodate quantitative and mixed covariates. Given a set of covariates, the user can generate a single sequence of allocations or replicate the design multiple times by simulating the patients' covariate profiles. At the end, an extensive assessment of the performance of the randomization procedures is provided, calculating several imbalance measures. See Baldi Antognini A, Frieri R, Zagoraiou M and Novelli M (2022) for details.
2023
Rosamarie Frieri, Marco Novelli (2023). R package "covadap".
Rosamarie Frieri; Marco Novelli
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/950255
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