Clinical Trial related calculation: descriptive statistics, power and sample size calculation, randomization.
Author PharmCat
14 Stars
Updated Last
12 Months Ago
Started In
January 2019


Clinical trial related calculation: power and sample size calculation, randomization. This program comes with absolutely no warranty. No liability is accepted for any loss and risk to public health resulting from use of this software.

Tier 1


Latest docs


using Pkg; Pkg.add("ClinicalTrialUtilities");

Main features

  • Clinical trial sample size calculation
  • Power calculation
  • Randomization



NB! Hypothesis types:

  • :ea - Equality: two-sided;
  • :ei - Equivalencens: two one-sided hypothesis (TOST);
  • :ns - Non-Inferiority / Superiority: one-sided hypothesis, for some cases you should use two-sided hypothesis for Non-Inferiority/Superiority, you can use alpha/2 for this;
#Sample size for one proportion equality
ctsamplen(param=:prop, type=:ea, group=:one, a=0.3, b=0.5)

#Equivalence for two means
ctsamplen(param=:mean, type=:ei, group=:two, diff=0.3, sd=1, a=0.3, b=0.5)

#Odd ratio non-inferiority
ctsamplen(param=:or, type=:ns, diff=-0.1, a=0.3, b=0.5, k=2)

#Odd ratio equality
ctsamplen(param=:or, type=:ea, a=0.3, b=0.5, k=2)

Bioequivalence sample size

besamplen(alpha=0.05,  theta1=0.8, theta2=1.25, theta0=0.95, cv=0.15, method=:owenq)
besamplen(cv=0.20, method=:nct)
besamplen(cv=0.347, design=:parallel)
besamplen(cv=0.347, design=:d2x2x4, method=:nct)


ctpower(param=:mean, type=:ea, group=:one, a=1.5, b=2, sd=1,n=32, alpha=0.05)

Bioequivalence power

#2x2 design, default method - OwensQ
bepower(alpha=0.05, logscale=true, theta1=0.8, theta2=1.25, theta0=0.95, cv=0.2, n=20, design=:d2x2, method=:owenq)

bepower(alpha=0.05, cv=0.2, n=20, design=:d2x2)

#Bioequivalence power for cv 14%, 21 subjects, default OwensQ method, logscale false
bepower(alpha=0.1, logscale=false, theta1=-0.1, theta2=0.1, theta0=0, cv=0.14, n=21)

#Bioequivalence power for cv 14%, 21 subjects, shifted method, logscale false
bepower(alpha=0.1, logscale=false, theta1=-0.1, theta2=0.1, theta0=0, cv=0.14, n=21, method=:shifted)

#Simple notations
bepower(cv=0.4, n=35, design=:d2x4x4)
bepower(cv=0.14, n=21)

Bioequivalence CV from CI

cvfromci(;alpha = 0.05, theta1 = 0.9, theta2 = 1.25, n=30, design=:d2x2x4)

Polled CV

data = DataFrame(cv = Float64[], df = Int[])
push!(data, (0.12, 12))
push!(data, (0.2, 20))
push!(data, (0.25, 30))
pooledcv(data; cv=:cv, df=:df, alpha=0.05, returncv=true)

pooledcv([0.12, 0.2, 0.25], [14, 22, 32], [:d2x2, :d2x2, :d2x2])


using DataFrames, ClinicalTrialUtilities
rt = ClinicalTrialUtilities.randomtable(;blocksize = 4, subject = 32, group = 2, ratio = [1,1], grseq = ["TR", "RT"], seed = 36434654652452)

Confidence Intervals

Proportion CI moved to MetidaFreq.jl


NCA moved to MetidaNCA.jl


Clinical Trial Utilities

Copyright © 2019 Vladimir Arnautov aka PharmCat (

If you want to check and get R code for power/sample size estimation, you can find examples here:

Used By Packages

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