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\name{Titanic}
\alias{Titanic}
\docType{data}
\title{Survival of Passengers on the Titanic}
\description{
Information on the survival status, sex, age, and passenger class of 1309
passengers in the Titanic disaster of 1912.
}
\usage{Titanic}
\format{
A data frame with 1309 observations on the following 4 variables.
\describe{
\item{\code{survived}}{\code{no} or \code{yes}.}
\item{\code{sex}}{\code{female} or \code{male}}
\item{\code{age}}{in years (and for some children, fractions of a year); age
is missing for 263 of the passengers.}
\item{\code{passengerClass}}{\code{1st}, \code{2nd}, or \code{3rd} class.}
}
}
\details{
This is part of a larger data set compiled by Thomas Cason.
Many additional details are given in the sources cited below.
}
\source{
Data set \code{titanic3} from
\url{http://biostat.mc.vanderbilt.edu/twiki/bin/view/Main/DataSets}.
}
\references{
\url{http://www.encyclopedia-titanica.org/}
F. E. Harrell, Jr. (2001)
\emph{Regression Modeling Strategies}
New York: Springer.
}
\examples{
summary(Titanic)
titanic <- glm(survived ~ (passengerClass + sex + age)^2, data=Titanic, family=binomial)
titanic.all <- allEffects(titanic, typical=median,
given.values=c(passengerClass2nd=1/3, passengerClass3rd=1/3, sexmale=0.5))
plot(titanic.all, ticks=list(at=c(.01, .05, seq(.1, .9, by=.2), .95, .99)), ask=FALSE)
plot(effect("passengerClass*sex*age", titanic, xlevels=list(age=0:65)),
ticks=list(at=c(.001, .005, .01, .05, seq(.1, .9, by=.2), .95, .99, .995)))
}
\keyword{datasets}
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