preference: An R Package for Two-Stage Clinical Trial Design Accounting for Patient Preference
Dublin Core
Title
preference: An R Package for Two-Stage Clinical Trial Design Accounting for Patient Preference
Subject
two-stage clinical trials, preference, sample size.
Description
The consideration of a patient’s treatment preference may be essential in determining
how a patient will respond to a particular treatment. While traditional clinical trials are
unable to capture these effects, the two-stage randomized preference design provides an
important tool for researchers seeking to understand the role of patient preferences. In
addition to the treatment effect, these designs seek to estimate the role of preferences
through testing of selection and preference effects. The R package preference facilitates
the use of two-stage clinical trials by providing the necessary tools to design and analyze
these studies. To aid in the design, functions are provided to estimate the required sample
size and to estimate the study power when a sample size is fixed. In addition, analysis
functions are provided to determine the significance of each effect using either raw data or
summary statistics. The package is able to incorporate either an unstratified or stratified
preference design. The functionality of the package is demonstrated using data from
a study evaluating two management methods in women found to have an atypical Pap
smear
how a patient will respond to a particular treatment. While traditional clinical trials are
unable to capture these effects, the two-stage randomized preference design provides an
important tool for researchers seeking to understand the role of patient preferences. In
addition to the treatment effect, these designs seek to estimate the role of preferences
through testing of selection and preference effects. The R package preference facilitates
the use of two-stage clinical trials by providing the necessary tools to design and analyze
these studies. To aid in the design, functions are provided to estimate the required sample
size and to estimate the study power when a sample size is fixed. In addition, analysis
functions are provided to determine the significance of each effect using either raw data or
summary statistics. The package is able to incorporate either an unstratified or stratified
preference design. The functionality of the package is demonstrated using data from
a study evaluating two management methods in women found to have an atypical Pap
smear
Creator
Briana Cameron
Source
https://www.jstatsoft.org/article/view/v094c02
Publisher
23andMe
Date
June 2020
Contributor
Fajar bagus W
Format
PDF
Language
Inggris
Type
Text
Files
Collection
Citation
Briana Cameron, “preference: An R Package for Two-Stage Clinical Trial Design Accounting for Patient Preference,” Repository Horizon University Indonesia, accessed April 11, 2025, https://repository.horizon.ac.id/items/show/8150.