CVfromCI: CV from a given Confidence interval

Description

Calculates the CV (coefficient of variation) from a known confidence interval of a BE study. Useful if no CV but the 90% CI was given in literature.

Usage

CVfromCI(point, lower, upper, n, design = "2x2", alpha = 0.05, robust=FALSE)
CI2CV(point, lower, upper, n, design = "2x2", alpha = 0.05, robust=FALSE)

Arguments

point

Point estimator of the BE ratio. The point estimator can be missing. In that case it will be calculated as geometric mean of lower and upper.

lower

Lower confidence limit of the BE ratio.

upper

Upper confidence limit of the BE ratio.

Total number of subjects under study if given as scalar. Number of subjects in (sequence) groups if given as vector.

design

Character string describing the study design. See known.designs() for designs covered in this package.

alpha

Error probability. Set it to (1-confidence)/2. Is 0.05 for the usual 90% confidence intervals.

robust

With robust=FALSE the usual degrees of freedom of the designs are used. With robust=TRUE the degrees of freedom for the so-called robust evaluation (df2 in known.designs()) will be used. This may be helpful if the CI was evalua

Value

Numeric value of the CV as ratio.

Details

See Helmut Schuetz lectures at www.bebac.at/lectures.htm for a description of the algebra underlying this function.

Examples

Run this code

# Given a 90\% confidence interval (without point estimator) 
# from a classical 2x2 crossover with 22 subjects
CVfromCI(lower=0.91, upper=1.15, n=22, design="2x2")
# will give [1] 0.2279405, i.e a CV ~ 23\%
#
# unbalanced 2x2 crossover study, but not reported as  such
CI2CV(lower=0.89, upper=1.15, n=24)
# will give a CV ~ 26.3\%
# unbalancedness accounted for
CI2CV(lower=0.89, upper=1.15, n=c(16,8))
# should give CV ~ 24.7\%