predlinear {LW1949} | R Documentation |
Determine the Effective Dose from a Linear Regression Fit
Description
Determine the effective dose for a specified percent effect from the intercept and slope of a linear regression.
Usage
predlinear(pct, LWmod, simple = FALSE)
Arguments
pct |
A numeric vector of effects (in percents) for which to estimate the effective dose(s). |
LWmod |
If |
simple |
A logical scalar indicating whether to carry out a simple estimation of effective doses from the intercept and slope (TRUE), or an estimation of effective doses with confidence intervals from the Litchfield and Wilcoxon model (default, FALSE). |
Details
Follows methods outlined in Litchfield and Wilcoxon (1949). Specifically, for the 95% confidence intervals, see page 105, and equation 13 in the Appendix (corresponding to Nomograph 4).
Value
If simple=TRUE
, a numeric vector the same length as pct
with
the estimated effective doses.
If simple=FALSE
, an n*4 numeric matrix with the given effects
(pct
), the effective doses (ED
), and Litchfield and
Wilcoxon's (1949) 95% confidence intervals for the effective doses
(lower
and upper
).
The number of rows of the matrix, n, is the length of pct
.
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].
Examples
predlinear(c(16, 50, 84, 99.9), c(1.700875, 2.199559), simple=TRUE)
dose <- c(0.0625, 0.125, 0.25, 0.5, 1)
ntested <- rep(8, 5)
nalive <- c(1, 4, 4, 7, 8)
mydat <- dataprep(dose=dose, ntot=ntested, nfx=nalive)
fLW <- LWestimate(fitLWauto(mydat), mydat)
predlinear(c(25, 50, 99.9), fLW)