PRMas: Analytical sample size calculation for PRM design problem

In baolinwu/SPprm: Statistical methods with power calculation for paired repeated measures comparisons: application to pulse oximetry studies

Description

Due to discrete nature of sample size, the power is not a continuous function. This function utilizes the analytical power calculation function PRSap() to compute an approximate sample size n under a given m (number of measures per unit), which has power closest to the desired power.

Usage

PRMas(pwr = 0.8, alpha = 0.05, m, s2w, s2b, mu, rho, REML = TRUE)

Arguments

pwr	desired power. Default to 0.8
alpha	desired significance level. Default to 0.05
m	number of repeated measures for each subject
s2w	within subject variation
s2b	between subject variation
mu	mean measure difference
rho	null threshold of acceptable RMS value
REML	using REML instead of MLE. Default to TRUE.

Value

n

computed number of units

pwr

actual power under the computed sample size

References

Bai,Y., Wang,Z., Lystig,T.C., and Wu,B. (2018) Statistical test with sample size and power calculation for paired repeated measures designs of method comparison studies.

baolinwu/SPprm documentation built on May 9, 2019, 8:41 a.m.