Package: preference 1.1.5

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> <doi:10.1002/sim.7830>

Authors:Briana Cameron [aut, cph], Denise Esserman [ctb], Michael Kane [cre, ctb]

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Bug tracker:https://github.com/kaneplusplus/preference/issues

On CRAN:

clinical-trial-designclinical-trialspreference-design

19 exports 2 stars 0.96 score 36 dependencies 11 scripts 523 downloads

Last updated 4 years agofrom:e0f11a502d. Checks:OK: 1 NOTE: 6. Indexed: yes.

Exports:effect_sizeeffects_from_meansfit_preferencefit_preference_summaryoptimal_proportionoverall_power_binomoverall_sample_size_binoverall_sample_size_poispowerpreferencepreference.trialproportionpt_from_powerpt_from_sspwr_overall_poissample_sizesigma2significancetreatment_effect_size

Dependencies:clicolorspacecpp11dplyrfansifarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigpurrrR6RColorBrewerrlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr