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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manual.pdf |manual.html✨
card.svg |card.png
preference/json (API)
NEWS

# Install 'preference' in R:
install.packages('preference', repos = c('https://kaneplusplus.r-universe.dev', 'https://cloud.r-project.org'))

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

Datasets:

On CRAN:

Conda:

clinical-trial-designclinical-trialspreference-design

3.22 score 3 stars 11 scripts 183 downloads 19 exports 29 dependencies

Last updated from:e0f11a502d. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE137
source / vignettesOK170
linux-release-x86_64NOTE113
macos-release-arm64NOTE168
macos-oldrel-arm64NOTE194
windows-develNOTE83
windows-releaseNOTE87
windows-oldrelNOTE86
wasm-releaseOK98

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:clicpp11dplyrfarvergenericsggplot2gluegtableisobandlabelinglifecyclemagrittrpillarpkgconfigpurrrR6RColorBrewerrlangS7scalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Design and Analysis of Two-stage Randomized Clinical Trialspreference-package
Calculate Effect Sizes from Meanseffects_from_means
Fit the Preference Data Collected from a Two-stage Clinical Trialfit_preference
Fit Preference Model from Summary Datafit_preference_summary
Data from the IMAP studyimap imap_stratified_summary imap_summary
Unstratified Optimized Thetaoptimal_proportion
Power Calculation from Sample Sizeoverall_power_binom
Overall Sample Size Binomialoverall_sample_size_bin
Overall Sample Size Poisson Distributionoverall_sample_size_pois
Plot the effect sizes of a preference trialplot.preference.trial
Fit Preference Data Collected from a Two-stage Clinical Trialpreference
Create a Preference Trialpreference.trial
Design Preference Trials with Power Constraint(s)pt_from_power
Design Preference Trials with Sample Size Constraint(s)pt_from_ss
Power Calculation from Sample Sizepwr_overall_pois
Preference trial parameter accessorseffect_size effect_size.preference.trial power power.preference.trial proportion proportion.preference.trial sample_size sample_size.preference.trial sigma2 sigma2.preference.trial significance significance.preference.trial
Treatment Effect Back Calculationtreatment_effect_size