The practical application of likelihood ratio test based interval esti
mates for L(50), ED(50), and related quantities is considered. Our mat
hematical setting is that of a generalized linear model with a known s
cale parameter. We extend the results of Williams (1986, Biometrics 42
, 641-645) by showing how Newton's method can be used to calculate the
end points of the intervals. To accommodate epidemiologic application
s we permit other explanatory variables besides those related to dose
in our model. We illustrate the use of the methods in a case in which
there are two sources of exposure, whose joint impact is of interest.
We also discuss the computation of the confidence sets, when they cons
ist of the whole real line or when they are unions of disjoint interva
ls. Special problems connected with the cases in which some of the max
imum likelihood estimators do not exist are studied. Simulation is use
d to compare the adequacy of the likelihood ratio based approach to th
at of the classical Fieller limits. The Fieller limits frequently fail
to exist in small samples. The likelihood ratio-based limits always e
xist, but they are sometimes slightly too narrow. The likelihood ratio
-based limits appear not to be as often infinite as the Fieller limits
are.