q.samp.size.long: Sample size for comparing means for longitudinal data

In qwickmalik/qwickr: A Quick and Easy Way to Analyze and Report Phase I-IV Clinical Trial Data including Pharmacokinetics

Sample size for comparing means for longitudinal data

Description

Calculate sample size for comparing mean changes for longitudinal data involving 2 time points based on powerMediation::ssLongFull

Usage

q.samp.size.long(ref.mean=NULL, comp.mean=NULL, baseline.sd=NULL, 
                endline.sd=NULL, dropout=0.2, arms=2, rho=0.5,
                sig.level = 0.05 , power = 0.8)

Arguments

ref.mean	Mean for change in values within a treatment group
comp.mean	Mean for change in values within the comparison group
baseline.sd	Standard deviation for baseline values
endline.sd	Standard deviation for end-of-study/follow-up values
dropout	Dropout rate to be accounted for in sample size calculation. Default is 0.2
arms	Number of arms in the planned study
rho	Correlation coefficient between baseline and follow-up values within a treatment group. Default is 0.5
sig.level	Significance level. Default is 0.05
power	Power. Default is 0.8

Value

A list containing the mean difference, mean ratio, number of completers per arm, total sample size per arm, total sample size for the study and number of study arms

Author(s)

Abdul Malik Sulley <[e-mail]> May 8, 2020

See Also

powerMediation::ssLongFull

Examples

ref.mean <- 57.2
comp.mean <- 22.8
baseline.sd <- 21.1
endline.sd <- 32.2
q.samp.size.long(ref.mean, comp.mean, baseline.sd, endline.sd, dropout=0.2)

qwickmalik/qwickr documentation built on March 30, 2022, 2:59 p.m.