R: 2-Stage Preference Trial Design and Analysis

# 2-Stage Preference Trial Design and Analysis

## Documentation for package ‘preference’ version 1.1.6

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

preference-package | Design and Analysis of Two-stage Randomized Clinical Trials
effects_from_means | Calculate Effect Sizes from Means
effect_size | Preference trial parameter accessors
effect_size.preference.trial | Preference trial parameter accessors
fit_preference | Fit the Preference Data Collected from a Two-stage Clinical Trial
fit_preference_summary | Fit Preference Model from Summary Data
imap | Data from the IMAP study
imap_stratified_summary | Data from the IMAP study
imap_summary | Data from the IMAP study
optimal_proportion | Unstratified Optimized Theta
overall_power_binom | Power Calculation from Sample Size
overall_sample_size_bin | Overall Sample Size Binomial
overall_sample_size_pois | Overall Sample Size Poisson Distribution
plot.preference.trial | Plot the effect sizes of a preference trial
power | Preference trial parameter accessors
power.preference.trial | Preference trial parameter accessors
preference | Fit Preference Data Collected from a Two-stage Clinical Trial
preference.trial | Create a Preference Trial
proportion | Preference trial parameter accessors
proportion.preference.trial | Preference trial parameter accessors
pt_from_power | Design Preference Trials with Power Constraint(s)
pt_from_ss | Design Preference Trials with Sample Size Constraint(s)
pwr_overall_pois | Power Calculation from Sample Size
sample_size | Preference trial parameter accessors
sample_size.preference.trial | Preference trial parameter accessors
sigma2 | Preference trial parameter accessors
sigma2.preference.trial | Preference trial parameter accessors
significance | Preference trial parameter accessors
significance.preference.trial | Preference trial parameter accessors
treatment_effect_size | Treatment Effect Back Calculation