Package: lordif
Type: Package
Title: Logistic Ordinal Regression Differential Item Functioning using
IRT
Version: 0.3-3
Date: 2016-03-3
Author: Seung W. Choi, with contributions from Laura E. Gibbons and
Paul K. Crane
Maintainer: Seung W. Choi <choi.phd@gmail.com>
Description: Analysis of Differential Item Functioning (DIF) for
dichotomous and polytomous items using an iterative hybrid of
ordinal logistic regression and item response theory (IRT).
Depends: R (>= 2.7.0), mirt, rms
Imports: stats4
License: GPL (>= 2)
LazyLoad: yes
NeedsCompilation: no
Packaged: 2016-03-03 03:58:22 UTC; Seung Choi
Repository: CRAN
Date/Publication: 2016-03-03 05:56:21
Package: mirtCAT
Version: 0.9
Date: 2016-06-24
Type: Package
Title: Computerized Adaptive Testing with Multidimensional Item
Response Theory
Authors@R: c( person("Phil", family="Chalmers", email =
"rphilip.chalmers@gmail.com", role = c("aut", "cre", "cph")))
Description: Provides tools to generate an HTML interface for creating adaptive
and non-adaptive educational and psychological tests using the shiny
package. Suitable for applying unidimensional and multidimensional
computerized adaptive tests using item response theory methodology and for
creating simple questionnaires forms to collect response data directly in R.
Package also contains tools useful for performing Monte Carlo simulations
for studying the behaviour of computerized adaptive test banks.
Depends: mirt (>= 1.18), shiny (>= 0.13.0)
Imports: lattice, stats, Rcpp, methods, markdown
Suggests: parallel, SimDesign, knitr
ByteCompile: no
LazyLoad: yes
LazyData: yes
VignetteBuilder: knitr
LinkingTo: Rcpp, RcppArmadillo
License: GPL (>= 3)
Repository: CRAN
Maintainer: Phil Chalmers <rphilip.chalmers@gmail.com>
URL: https://github.com/philchalmers/mirtCAT,
https://github.com/philchalmers/mirtCAT/wiki
BugReports: https://github.com/philchalmers/mirtCAT/issues?state=open
RoxygenNote: 5.0.1
NeedsCompilation: yes
Packaged: 2016-06-24 06:34:40 UTC; phil
Author: Phil Chalmers [aut, cre, cph]
Date/Publication: 2016-06-24 09:53:49
Package: NominalLogisticBiplot
Type: Package
Title: Biplot representations of categorical data
Version: 0.2
Date: 2014-05-01
Author: Julio Cesar Hernandez Sanchez, Jose Luis Vicente-Villardon
Maintainer: Julio Cesar Hernandez Sanchez <juliocesar_avila@usal.es>
Description: Analysis of a matrix of polytomous items using Nominal Logistic Biplots (NLB)
according to Hernandez-Sanchez and Vicente-Villardon (2013).
The NLB procedure extends the binary logistic biplot to nominal (polytomous) data.
The individuals are represented as points on a plane and the variables are represented
as convex prediction regions rather than vectors as in a classical or binary biplot.
Using the methods from Computational Geometry, the set of prediction regions is converted to a set of points
in such a way that the prediction for each individual is established by its closest
"category point". Then interpretation is based on distances rather than on projections.
In this package we implement the geometry of such a representation and construct computational algorithms
for the estimation of parameters and the calculation of prediction regions.
License: GPL (>= 2)
Encoding: latin1
Repository: CRAN
Depends: R (>= 2.15.1), mirt, gmodels, MASS
LazyData: yes
Archs: i386, x64
NeedsCompilation: no
Packaged: 2014-05-01 20:17:23 UTC; Julio César
Date/Publication: 2014-05-02 07:13:20
Package: OrdinalLogisticBiplot
Type: Package
Title: Biplot representations of ordinal variables
Version: 0.4
Date: 2015-15-01
Author: Julio Cesar Hernandez Sanchez, Jose Luis Vicente-Villardon
Maintainer: Julio Cesar Hernandez Sanchez <juliocesar_avila@usal.es>
Description: Analysis of a matrix of polytomous items using Ordinal Logistic Biplots (OLB)
The OLB procedure extends the binary logistic biplot to ordinal (polytomous) data.
The individuals are represented as points on a plane and the variables are represented
as lines rather than vectors as in a classical or binary biplot, specifying the points
for each of the categories of the variable.
The set of prediction regions is established by stripes perpendicular to the line
between the category points, in such a way that the prediction for each individual is given
by its projection into the line of the variable.
License: GPL (>= 2)
Encoding: latin1
Repository: CRAN
Depends: R (>= 2.15.1), mirt, MASS, NominalLogisticBiplot
LazyData: yes
Archs: i386, x64
NeedsCompilation: no
Packaged: 2015-01-16 18:48:23 UTC; Julio César
Date/Publication: 2015-01-16 22:11:44
Package: PerFit
Type: Package
Title: Person Fit
Version: 1.4
Date: 2015-07-13
Author: Jorge N. Tendeiro
Maintainer: Jorge N. Tendeiro <j.n.tendeiro@rug.nl>
Description: Several person-fit statistics (PFSs) are offered. These statistics allow assessing whether
individual response patterns to tests or questionnaires are (im)plausible given
the other respondents in the sample or given a specified item response theory model. Some PFSs apply to
dichotomous data, such as the likelihood-based PFSs (lz, lz*) and the group-based PFSs
(personal biserial correlation, caution index, (normed) number of Guttman errors,
agreement/disagreement/dependability statistics, U3, ZU3, NCI, Ht). PFSs suitable to polytomous data include
extensions of lz, U3, and (normed) number of Guttman errors.
Imports: stats, graphics, fda, Hmisc, irtoys, MASS, Matrix
Depends: ltm, mirt
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2015-07-17 07:03:15 UTC; p250795
Repository: CRAN
Date/Publication: 2015-07-20 09:59:35
providing 
.