a research synthesis with correlational data. One of the unique
features of this package is in its integration of user-friendly
functions to complete all statistical steps involved in a meta-
analysis with correlations. It uses recommended procedures as
described in The Handbook of Research Synthesis and
Meta-Analysis (Cooper, Hedges, & Valentine, 2009).

functions to complete all statistical steps involved in a
meta-analysis with correlations. It uses recommended procedures
as described in The Handbook of Research Synthesis and

functions to complete the majority of statistical steps
involved in a meta-analysis with correlations. It uses
recommended procedures as described in The Handbook of Research
Synthesis and Meta-Analysis (Cooper, Hedges, & Valentine,

a correlational research synthesis. One of the unique features
of this package is in its integration of user-friendly
functions to facilitate statistical analyses at each stage in a

Description: This is an integrated package for conducting all required
steps in a meta-analysis with correlations. It uses recommended
procedures as described in Cooper, Hedges, & Valentine's
Handbook of Research Synthesis and Meta-Analysis (2009).

Title: Class prediction based on microarray data and clinical parameters
Depends: R (>= 2.4.1), party, plsgenomics, st, e1071
Description: 'Maclinical' implements class prediction using both microarray data and clinical parameters. It addresses the question of the additional predictive value of microarray data.  Class prediction is performed using a two-step method combining (pre-validated) PLS dimension reduction and random forests.
Packaged: Sun Sep 28 20:15:40 2008; hornik

Title: Class prediction based on microarray data and clinical
Description: 'Maclinical' implements class prediction using both
microarray data and clinical parameters. It addresses the
question of the additional predictive value of microarray data.
Class prediction is performed using a two-step method combining
(pre-validated) PLS dimension reduction and random forests.