overall_power: Power Calculation from Sample Size In preference: 2-Stage Preference Trial Design and Analysis

Description

Calculates the study power to detect a set of effects given a particular sample size in a two-stage randomized clinical trial

Usage

 ```1 2``` ```overall_power(N, phi, sigma2, delta_pi, delta_nu, delta_tau, alpha = 0.05, theta = 0.5, xi = 1, nstrata = 1, k = 1) ```

Arguments

 `N` overall study sample size. `phi` the proportion of patients preferring treatment 1. Should be numeric value between 0 and 1. If study is stratified, should be vector with length equal to the number of strata in the study. `sigma2` variance estimate. Should be positive numeric values. If study is stratified, should be vector of within-stratum variances with length equal to the number of strata in the study. `delta_pi` overall study preference effect. `delta_nu` overall study selection effect. `delta_tau` overall study treatment effect. `alpha` desired type I error rate. `theta` proportion of patients assigned to choice arm in the initial randomization. Should be numeric value between 0 and 1 (default=0.5). `xi` a numeric vector of the proportion of patients in each stratum. Length of vector should equal the number of strata in the study and sum of vector should be 1. All vector elements should be numeric values between 0 and 1. Default is 1 (i.e. unstratified design). `nstrata` number of strata. Default is 1 (i.e. unstratified design). `k` the ratio of treatment A to treatment B in the random arm (default 1).

References

Turner RM, et al. (2014). "Sample Size and Power When Designing a Randomized Trial for the Estimation of Treatment, Selection, and Preference Effects." Medical Decision Making, 34:711-719. (PubMed)

Cameron B, Esserman D (2016). "Sample Size and Power for a Stratified Doubly Randomized Preference Design." Stat Methods Med Res. (PubMed)

preference documentation built on Nov. 30, 2018, 4:22 p.m.