<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>rfrieri91-sys.r-universe.dev</title><link>https://rfrieri91-sys.r-universe.dev</link><description>Recent package updates in rfrieri91-sys</description><generator>R-universe</generator><image><url>https://github.com/rfrieri91-sys.png</url><title>R packages by rfrieri91-sys</title><link>https://rfrieri91-sys.r-universe.dev</link></image><lastBuildDate>Thu, 07 Dec 2023 02:39:56 GMT</lastBuildDate><item><title>[rfrieri91-sys] covadap 1.0.1</title><author>rosamarie.frieri2@unibo.it (Rosamarie Frieri)</author><description>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) &lt;doi:10.1007/s00362-022-01381-1&gt; for details.</description><link>https://github.com/r-universe/rfrieri91-sys/actions/runs/27191778961</link><pubDate>Thu, 07 Dec 2023 02:39:56 GMT</pubDate><r:package>covadap</r:package><r:version>1.0.1</r:version><r:status>success</r:status><r:repository>https://rfrieri91-sys.r-universe.dev</r:repository><r:upstream>https://github.com/cran/covadap</r:upstream></item></channel></rss>