relPotency function

Relative Potency of Two Toxins

Estimate of relative potency of two toxins using Litchfield and Wilcoxon's (1949) approach to evaluating dose-effect experiments.

relPotency(ED50nS1, ED50nS2, vec = FALSE)

Arguments

• ED50nS1: Either the list output from LWestimate (vec = FALSE) or a numeric vector of length four (vec = TRUE) with the estimated ED50, fED50, S, and fS from a Litchfield and Wilcoxon fit to dose-effect data for the first toxin.
• ED50nS2: Either the list output from LWestimate (vec = FALSE) or a numeric vector of length four (vec = TRUE) with the estimated ED50, fED50, S, and fS from a Litchfield and Wilcoxon fit to dose-effect data for the second toxin.
• vec: A logical scalar indicating whether the inputs ED50nS1 and ED50nS2 are both numeric vectors (TRUE) or both lists (FALSE, the default).

Returns

A list with two elements, SR with three elements:

• r = a numeric vector of length three with the estimated slope ratio with 95% confidence limits,
• f = a numeric scalar with the f of the slope ratio, and
• parallel = a logical scalar indicating whether the two curves differ significantly from parallelism (FALSE).

and PR with one (just difPotency if parallel=FALSE) or three (if parallel=TRUE) elements:

• r = a numeric vector of length three with the estimated potency ratio with 95% confidence limits,
• f = a numeric scalar with the f of the potency ratio, and
• difPotency = a logical scalar indicating whether the two toxins differ significantly in potency (FALSE).

Details

The ratios reported (both for slope and potency) have the first toxin in the numerator and the second toxin in the denominator, but the test results (both for parallelism and relative potency) are based on the ratios of the larger values over the smaller values.

No relative potency is estimated if the two dose-effect curves differ significantly from parallelism (with 95% confidence).

Examples

# Example starting from raw tox data
dose <- c(0.0625, 0.125, 0.25, 0.5, 1)
ntested <- rep(8, 5)
nalive1 <- c(1, 4, 4, 7, 8)
mydat1 <- dataprep(dose=dose, ntot=ntested, nfx=nalive1)
nalive2 <- c(0, 1, 2, 6, 6)
mydat2 <- dataprep(dose=dose, ntot=ntested, nfx=nalive2)
fit1 <- LWestimate(fitLWauto(mydat1), mydat1)
fit2 <- LWestimate(fitLWauto(mydat2), mydat2)
relPotency(fit1, fit2)

# Example from Litchfield and Wilcoxon (1949)
# comparing Tagathen and Pyribenzamine
relPotency(c(0.18, 1.72, 2.20, 1.60), c(0.60, 1.60, 2.34, 1.57), vec=TRUE)

# Example in which curves differ significantly from parallelism.
relPotency(c(0.18, 1.72, 2.20, 1.60), c(0.60, 1.60, 4.34, 1.57), vec=TRUE)

References

Litchfield, JT Jr. and F Wilcoxon. 1949. A simplified method of evaluating dose-effect experiments. Journal of Pharmacology and Experimental Therapeutics 96(2):99-113. [link].