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\name{carrots}
\alias{carrots}
\docType{data}
\title{Insect Damages on Carrots}
\description{
The damage carrots data set from Phelps (1982) was used by McCullagh
and Nelder (1989) in order to illustrate diagnostic techniques because
of the presence of an outlier. In a soil experiment trial with three
blocks, eight levels of insecticide were applied and the carrots were
tested for insect damage.
}
\usage{data(carrots, package="robustbase")}
\format{
A data frame with 24 observations on the following 4 variables.
\describe{
\item{success}{ integer giving the number of carrots with insect damage.}
\item{total}{ integer giving the total number of carrots per
experimental unit.}
\item{logdose}{a numeric vector giving log(dose) values (eight
different levels only).}
\item{block}{factor with levels \code{B1} to \code{B3}}
}
}
\source{
Phelps, K. (1982).
Use of the complementary log-log function to describe doseresponse
relationships in insecticide evaluation field trials.
\cr
In R. Gilchrist (Ed.), \emph{Lecture Notes in Statistics, No. 14.
GLIM.82: Proceedings of the International Conference on Generalized
Linear Models}; Springer-Verlag.
}
\references{
McCullagh P. and Nelder, J. A. (1989)
\emph{Generalized Linear Models.}
London: Chapman and Hall.
Eva Cantoni and Elvezio Ronchetti (2001); JASA, and \cr
Eva Cantoni (2004); JSS, see \code{\link{glmrob}}
}
\examples{
data(carrots)
str(carrots)
plot(success/total ~ logdose, data = carrots, col = as.integer(block))
coplot(success/total ~ logdose | block, data = carrots)
## Classical glm
Cfit0 <- glm(cbind(success, total-success) ~ logdose + block,
data=carrots, family=binomial)
summary(Cfit0)
## Robust Fit (see help(glmrob)) ....
}
\keyword{datasets}
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