\HeaderA{ssStatistic}{Calculate single study estimates of effect size}{ssStatistic}
\keyword{methods}{ssStatistic}
\begin{Description}\relax
Calculate single study estimates of effect size for lists of \code{ExpressionSets}
\end{Description}
\begin{Usage}
\begin{verbatim}
ssStatistic(statistic = c("t", "sam", "z")[1], phenotypeLabel, esetList, ...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{statistic}] Character string indicating Welch t-statistic (t), SAM (sam), or a z-statistic (z)
\item[\code{phenotypeLabel}] Character string indicating the name of the binary covariate
\item[\code{esetList}] An object of class \code{ExpressionSetList}
\item[\code{...}] Not implemented. Potentially additional arguments to the
above methods that are implemented in other packages
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
This function is a wrapper that provides an estimate of effect size
for each study (element) in an \code{ExpressionSetList} object.

For Welch t-statistic, this function is a wrapper for mt.teststat in the
multtest package.

For SAM, this function is a wrapper for the sam function in the
siggenes package.

The "z" statistic is a standardized unbiased estimate of effect size
(Hedges and Olkin, 1985) -- implementation is in the zScores
function in the R package GeneMeta.

See the complete references below.
\end{Details}
\begin{Value}
A matrix: rows are genes and columns are studies
\end{Value}
\begin{Author}\relax
R. Scharpf
\end{Author}
\begin{References}\relax
J.K. Choi, U. Yu, S. Kim, and O.J. Yoo (2003), Combining multiple
microarray studies and modeling interstudy variation, Bioinformatics,
19(1) I84-I90.

Y. Ge, S. Dudoit \& T. P. Speed (2003), Resampling-based multiple testing
for microarray data hypothesis Test 12(1) : 1-44 (with discussions on
44-77).

L. Lusa R. Gentleman, and M. Ruschhaupt, GeneMeta: MetaAnalysis for High
Throughput Experiments

L.V. Hedges and I. Olkin, Statistical Methods for Meta-analysis
(1985), Academic Press

Tusher, Tibshirani and Chu (2001), Significance analysis of microarrays
applied to the ionizing radiation response, PNAS 2001 98: 5116-5121,
(Apr 24).
\end{References}
\begin{Examples}
\begin{ExampleCode}

data(expressionSetList)
if(require(multtest)){
  t <- ssStatistic("t", esetList=expressionSetList, phenotypeLabel="adenoVsquamous")
}  
\end{ExampleCode}
\end{Examples}

