n1.get.solution: Find minimal n1 achieving target power for range of values of...

In exact.n: Exact Samples Sizes and Inference for Clinical Trials with Binary Endpoint

Find minimal n1 achieving target power for range of values of p0

Description

This function calls n1.get.vector, runs if for all values of p0 within the supplied range and then takes the worst (i.e. largest) solution for n1

Usage

n1.get.solution(data, beta, p0, delta, alpha, type = 1)

Arguments

data	power database for selected value of alpha and delta
beta	scalar target for power
p0	single value or range of values for baseline probability
delta	value of clinically relevant difference
alpha	value of nominal size of test
type	type of minimum solution (See details)

Value

vector of solutions for n1 with name vector equal to range of n0 values

Author(s)

Chris J. Lloyd

References

C.J. Lloyd (2022) Exact samples sizes for clinical trials subject to size and power constraints. Preprint. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.13140/RG.2.2.11828.94085")}

Examples

# Load toy version of power library for alpha=0.025, delta=0.20.
rdata_file = system.file('files', 'LIB.a025.d20.Rdata', package = 'exact.n')
load(rdata_file)
# n0 solutions when p0=0.5
n1.get.solution(LIB.a025.d20,beta=.7,p0=0.5,delta=0.2,alpha=0.025,type=1)
# n0 solutions for p0 between 0.4 ad 0.5
n1.get.solution(LIB.a025.d20,beta=.7,p0=c(0.4,0.5),delta=0.2,alpha=0.025,type=1)

exact.n documentation built on Nov. 9, 2023, 9:06 a.m.