ci() calculates the confidence interval around observed values given a
coefficient of variation (CV).
Usage
ci(x, cv, dist = c("lognormal", "normal"), level = 0.95)Arguments
- x
A numeric vector of positive measured values.
- cv
A positive scalar: coefficient of variation (e.g., 0.10 for 10%).
- dist
A character scalar indicating the distributional assumption used to compute the confidence interval. Must be one of:
"normal": assumes measurement errors are normally distributed. The confidence interval will be symmetric around the observed value."lognormal": assumes measurement errors follow a log-normal distribution. This results in an asymmetric confidence interval, which is often more appropriate for strictly positive and right-skewed measurements (e.g., biomarker concentrations).
- level
Confidence level as a proportion (e.g., 0.95 for 95%). Default is 0.95.
Examples
# Lognormal assumption is often more appropriate for strictly positive
# and right-skewed measurements (e.g., biomarker concentrations).
ci(c(100, 200), 0.10, dist = "lognormal", level = 0.95)
#> lower upper
#> [1,] 82.24159 121.593
#> [2,] 164.48318 243.186
# Normal assumption
ci(c(100, 200), 0.10, dist = "normal", level = 0.95)
#> lower upper
#> [1,] 80.40036 119.5996
#> [2,] 160.80072 239.1993