\name{JT.test}
\alias{JT.test}
\title{Jonckheere-Terpstra trend test}

\description{The test is testing for a monotone trend in terms of the class parameter.
             The number of times that an individual of a higher class has a higher gene expression forms a basis for the inference.}

\usage{trendA <- JT.test(data, class, labs = c("NS", "HS", "COPD0", "COPD1", "COPD2"), alternative = c("increasing", "decreasing", "two-sided"))}

\arguments{
\item{data}{A matrix with genes in rows and subjects in columns}
\item{class}{the column labels, if not an ordered fctor it will be redefined to be one.}
\item{labs}{the labels of the categories coded by class}
}

\value{an object of class JT-test, which extends the class htest, and includes the following slots
\item{statistic}{the observed JT statistic}
\item{parameter}{the null hypothesis parameter, if other value than 0.}
\item{p.value}{the p-value for the two-sided test of no trend.}
\item{method}{Jonckheere-Terpstra}
\item{alternative}{The relations between the levels: decreasing, increasing or two-sided}
\item{data.name}{the name of the input data}
\item{median1 ... mediann}{the medians for the n groups}
\item{trend}{the rank correlation with category}
\item{S1}{Predictive strength}
}

\details{Assumes that groups are given in increasing order, if the class variable is not an ordered factor, it will be redefined to be one. The p-value
is calculated through a normal approximation.\cr

The implementation owes to suggestions posted to R list. \cr

The definition of predictive strength appears in Flandre and O'Quigley.}


\examples{
# Enter the data as a vector
A <- as.matrix(c(99,114,116,127,146,111, 125,143,148,157,133,139, 149, 160, 184))
# create the class labels
g <- c(rep(1,5),rep(2,5),rep(3,5))
# The groups have the medians
tapply(A, g, median)
# JT.test indicates that this trend is significant at the 5% level
JT.test(data = A, class = g, labs = c("GRP 1", "GRP 2", "GRP 3"), alternative = "two-sided")
}

\author{Per Broberg, acknowledging input from Christopher Andrews at SUNY Buffalo}

\references{
Lehmann, EH (1975) \emph{Nonparametrics: Statistical Methods Based on Ranks} p. 233. Holden Day \cr
Flandre, Philippe and O'Quigley, John, \emph{Predictive strength of Jonckheere's test for trend: an application to genotypic scores in HIV infection},
Statistics in Medicine, 2007, 26, 24, 4441-4454 } 

\keyword{nonparametric}