ss_po: Determine the sample size for Bayesian two-stage trial design...

In BayesOrdDesign: Bayesian Group Sequential Design for Ordinal Data

Determine the sample size for Bayesian two-stage trial design of ordinal endpoints with proportional odds assumption

Description

Obtain estimated sample size based on user-specified type I error, power and effect size defined by the odds ratio between the treatment and control groups, under the proportional odds (PO) assumption.

Usage

ss_po(or_alt, pro_ctr, alpha, power, nmax, ntrial, method)

Arguments

or_alt	effect size to be detected (under H_1) in terms of odds ratio
pro_ctr	distribution of clinical categories for the control group
alpha	the desirable type I error rate to be controlled
power	the desirable power to be achieved
nmax	the maximum sample size for searching to get the desirable power
ntrial	the number of simulated trials
method	whether the statistical test for interim/final analysis is Bayesian or Frequentist. method = "Frequentist" for Frequentist approach; method = "Bayesian" for Bayesian approach

Details

Grid search of sample size is used for guarantee a desirable type I error rate. The upper limitation is 200, and lower limitation default is sample size 50 for the control and treatment groups at each stage. Default increment of the sequence is 50.

For the parameter estimation section, we have two options, and can be selected using the method argument.Two following options are available: (i) method = "Frequentist", (ii) method = "Bayesian". If method = "Frequentist", parameters are estimated via package ordinal, which is based on frequentist method, while method = "Bayesian", parameters are estimated through Bayesian model.

Please note, in our example, argument ntrial = 5 is for the time saving purpose.

Value

ss_po() returns recommended sample size for each of two groups for the interim and final stages, by assuming 1:1 equal randomization for the two groups at each stage; and the corresponding power.

Examples

ss_po(or_alt = 1.5, pro_ctr = c(0.58,0.05,0.17,0.03,0.04,0.13), alpha = 0.05,
      power = 0.8, nmax = 100, ntrial = 5, method ="Frequentist")

BayesOrdDesign documentation built on Nov. 14, 2022, 5:07 p.m.