## ClinicalTrialUtilities.jl

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

# ClinicalTrialUtilities

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.

### Installation

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

### Main features

• Clinical trial sample size calculation
• Power calculation
• Randomization

### Examples

#### SampleSize

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=0.40)
besamplen(cv=0.347, design=:d2x2x4, method=:nct)
``````

#### Power

``````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)

#Same
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])

``````

#### Randomization

``````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

NCA moved to MetidaNCA.jl

Clinical Trial Utilities