R packages - Sep 2007 - New R package plink for separate calibration IRT linking

The first version of the package plink has been uploaded to CRAN.

plink is a package for conducting unidimensional IRT scaling and chain
linking for multiple groups for single-format or mixed-format common
items. The package supports eight IRT models and four calibration
methods.

Dichotomous Models:
1PL, 2PL, 3PL

Polytomous Models:
-Graded response model
-Partial credit model
-Generalized partial credit model
-Nominal response model
-Multiple-choice model

Calibration Methods:
-Mean/Mean
-Mean/Sigma
-Haebara
-Stocking-Lord

Any combination of dichotomous and polytomous items can be supplied
with intermingled unique and common items for as many items and groups
as system memory allows. Linking constants are computed and returned
for all the calibration methods, and (if desired) ability and/or item
parameters can be rescaled and returned using any of the estimated
linking constants.

Any of the included groups can be specified as the base scale, the
characteristic curve methods can use symmetric or non-symmetric
optimization, various scoring functions can be supplied for the
Stocking-Lord method, and there is great flexibility in specifying
thetas and theta weights to be integrated over in the characteristic
curve methods.

In addition to computing linking constants and rescaling ability and
item parameters, the methods in the package can be used to compute
item/category response probabilities and create plots of item/category
characteristic curves.

The package is designed to allow for a variety of formats for the item
parameters including vectors, lists, matrices, and other objects
(irt.pars and sep.pars) available in the package. Item parameters and
calibration output can be summarized, and descriptive statistics for
the item parameters can be displayed as well.

Getting Started:
Running the separate calibration is typically a two-step process. The
first step is to format the item parameters for processing with the
function 'plink'. Parameters should be formatted as either an object
of class 'irt.pars' with multiple groups, a set of 'irt.pars'
objects,
or a set of 'sep.pars' objects.  Once in this format, response
probabilities can be computed using the functions 'drm', 'gpcm',
'grm', 'mcm', or 'nrm' or linking constants can be
computed using
'plink'.

The functions 'as.irt.pars', 'sep.pars', and
'combine.pars' can be
used to create the 'irt.pars' and 'sep.pars' objects.
'summary' can be
used to summarize item parameters (including descriptive statistics)
and linking constants, and 'plot' can be used to create item/category
characteristic curves.

I am currently working on a vignette; however, the documentation
contains extensive examples. The best documentation to start with is
help(as.irt.pars) and help(plink).

Although this is the first version of this package, I have gone
through extensive debugging and validation, so there should be few, if
any bugs. Many of the examples (and the associated output) can be
found in published articles or books, and the output from the various
calibration methods has been checked against other available linking
software.

I hope this will be a useful package for those interested in test
linking. I invite any comments and suggestions.

Take care

-- 
Jonathan Weeks
Doctoral Candidate
School of Education
University of Colorado, Boulder
weeksjp at gmail.com
303-517-9666

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