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\name{scoreresid.msm}
\alias{scoreresid.msm}
\title{Score residuals}
\description{
Score residuals for detecting outlying subjects.
}
\usage{
scoreresid.msm(x, plot=FALSE)
}
\arguments{
\item{x}{A fitted multi-state model, as returned by
\code{\link{msm}}.}
\item{plot}{If \code{TRUE}, display a simple plot of the residuals in
subject order, labelled by subject identifiers}
}
\value{
Vector of the residuals, named by subject identifiers.
}
\details{
The score residual for a single subject is
\deqn{U(\theta)^T I(\theta)^{-1} U(\theta)}{U(theta)^T I(theta)^{-1} U(theta)}
where \eqn{U(\theta)}{U(theta)} is the vector of first derivatives of the
log-likelihood for that subject at maximum likelihood estimates
\eqn{\theta}{theta}, and \eqn{I(\theta)}{theta} is the observed Fisher
information matrix, that is, the matrix of second derivatives of minus
the log-likelihood for that subject at theta.
Subjects with a higher influence on the maximum likelihood estimates
will have higher score residuals.
}
\author{Andrew Titman \email{a.titman@lancaster.ac.uk} (theory),
Chris Jackson \email{chris.jackson@mrc-bsu.cam.ac.uk} (code)}
\keyword{models}
|
