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preference: 2-Stage Preference Trial Design and Analysis

Design and analyze two-stage randomized trials with a continuous outcome measure. The package contains functions to compute the required sample size needed to detect a given preference, treatment, and selection effect; alternatively, the package contains functions that can report the study power given a fixed sample size. Finally, analysis functions are provided to test each effect using either summary data (i.e. means, variances) or raw study data <doi:10.18637/jss.v094.c02>.

Version: 1.1.6
Imports: ggplot2, tidyr
Suggests: testthat
Published: 2020-09-09
Author: Briana Cameron [aut, cph], Denise Esserman [ctb], Michael Kane ORCID iD [cre, ctb]
Maintainer: Michael Kane <michael.kane at yale.edu>
BugReports: https://github.com/kaneplusplus/preference/issues
License: LGPL-2
URL: https://github.com/kaneplusplus/preference
NeedsCompilation: no
Citation: preference citation info
Materials: README NEWS
In views: CausalInference
CRAN checks: preference results

Documentation:

Reference manual: preference.pdf

Downloads:

Package source: preference_1.1.6.tar.gz
Windows binaries: r-devel: preference_1.1.6.zip, r-release: preference_1.1.6.zip, r-oldrel: preference_1.1.6.zip
macOS binaries: r-release (arm64): preference_1.1.6.tgz, r-oldrel (arm64): preference_1.1.6.tgz, r-release (x86_64): preference_1.1.6.tgz, r-oldrel (x86_64): preference_1.1.6.tgz
Old sources: preference archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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