As an advanced approach to computerized adaptive testing (CAT),
shadow testing (van der Linden(2005) <doi:10.1007/0-387-29054-0>) dynamically
assembles entire shadow tests as a part of
selecting items throughout the testing process.
Selecting items from shadow tests guarantees the compliance of all content
constraints defined by the blueprint. 'RSCAT' is an R package for the
shadow-test approach to CAT. The objective of
'RSCAT' is twofold: 1) Enhancing the effectiveness of shadow-test CAT simulation;
2) Contributing to the academic and scientific community for CAT research.
RSCAT is currently designed for dichotomous items based on the three-parameter logistic (3PL) model.

Symbolic Data Analysis (SDA) was proposed by professor
Edwin DIDAY in 1987, the main purpose of SDA is to substitute
the set of rows (cases) in the data table for a concept (second
order statistical unit). This package implements, to the
symbolic case, certain techniques of automatic classification,
as well as some linear models.

Oldemar Rodriguez R. with contributions from Johnny Villalobos
M.
R (>= 2.10), abind, RODBC, glmnet, ggplot2, scales,
scatterplot3d, FactoMineR

Oldemar Rodriguez R. with contributions from Olger Calderon and Roberto Zuniga
Symbolic Data Analysis (SDA) was proposed by professor Edwin Diday in 1987, the main purpose of SDA is to substitute the set of rows (cases) in the data table for  a concept (second order statistical unit). This package implements, to the symbolic case, certain techniques of automatic classification, as well as some linear models.
R (>= 2.10), sqldf, XML, scales, FactoMineR, ggplot2

Oldemar Rodriguez R. with contributions from Olger Calderon, Roberto Zuniga and Jorge Arce
R (>= 2.10), XML, scales, ggplot2, princurve, sqldf
RJSONIO, glmnet, abind, scatterplot3d, graphics, stats, utils,
FactoMineR

Oldemar Rodriguez R. with contributions from Carlos Aguero, Olger Calderon, Roberto Zuniga and Jorge Arce
RJSONIO, glmnet, abind, scatterplot3d, graphics, stats, utils,
FactoMineR, XML, scales, ggplot2, princurve, sqldf, dplyr,
tidyr, stringr, lazyeval