Utilities

cvfromci(;alpha = 0.05, theta1 = 0.8, theta2 = 1.25, n, design=:d2x2, mso=false, cvms=false)::AbstractFloat

CV from bioequivalence confidence inerval.

alpha - Alpha (o < alpha < 1) (default=0.05);

beta - Beta (o < beta < 1) (default=0.2); power = 1 - beta;

theta1 - Lower Level (default=0.8);

theta2 - Upper level (default=1.25);

n - subject n;

design - trial design;

• :parallel
• :d2x2 (default)
• :d2x2x4
• :d2x4x4
• :d2x3x3
• :d2x4x2
• :d3x3
• :d3x6x3

mso

Calculate MS only

• false(default)
• true

Deprecated:

cvms Calculate CV and MS

• false(default)
• true

cvfromsd(σ::Real)::AbstractFloat

CV from variance.

cvfromvar(σ²::Real)::AbstractFloat

CV from variance.

sdfromcv(cv::Real)::AbstractFloat

LnSD from CV.

varfromcv(cv::Real)::AbstractFloat

LnVariance from CV.

pooledcv(data; cv=:cv, df=:df, alpha=0.05, returncv=true)

Pooled CV from multiple sources.

data - data with CV data

cv::Symbol - CV column

df::Symbol - DF column

alpha - Alpha for var/cv confidence interval.

returncv - Return CV or var:

• true - return cv
• false - return var

Return tuple: (lower, upper, estimate).

Example:

data = DataFrame(cv = Float64[], df = Int[])
push!(data, (0.12, 12))
push!(data, (0.2, 20))
push!(data, (0.25, 30))
ci = ClinicalTrialUtilities.pooledcv(data; cv="cv", df="df")
println("Lower: ", ci[1])
println("Upper: ", ci[2])
println("Estimate: ", ci[3])

Lower: 0.18145259424967664
Upper: 0.2609307413637307
Estimate: 0.21393949168210136

pooledcv(cv::Vector, df::Vector; alpha = 0.05, returncv = true)

Pooled CV from multiple sources.

cv - CV Vector

df - DF Vector

alpha - Alpha for var/cv confidence interval.

returncv - Return CV or var:

• true - return cv
• false - return var

pooledcv(cv::Vector, n::Vector, design::Vector; alpha = 0.05, returncv = true)

Pooled CV from multiple sources.

cv - CV Vector

n - n Vector

design - design Vector

alpha - Alpha for var/cv confidence interval.

returncv - Return CV or var:

• true - return cv
• false - return var