Downloads
Presentations
Handouts and Slides from SIOP 2001 symposium "A Practical Guide to IRT: Introduction to Item Response Theory Analyses and Applications."
Programs
- Please extract zip files in your target folder (any folder you create).
- MODFIT plots theoretical item response functions and examine the
fit of dichotomous or polytomous IRT models to response data. You may review MODFIT instructions
here.
- ITERLINK performs iterative linking and pairwise DIF detection for the 3PL IRT model using Lord's chi-square. You may review ITERLINK instructions here.
- PARTO3PL (Win9x series), PAR_3PL (WinNT & Win2k series)
will convert original BILOG for DOS/Windows generated parameter file (*.PAR) in that folder, delete the first four lines (title/comment information) and subsequent alternating rows (standard errors),
and rename the files using the *.3PL extension by following the
32x,2f12.6,12x,f12.6 format (which can be used for running ITERLINK).
PAR_3PL will also retain 3 columns of a, b, c parameters only in a 3PL model (from columns 4, 5, and 7 of
the original BILOG's *.PAR file, and rename the file using the *.TXT
extension (free-field format), which is compatible with ParConversion.
- PAR3PLMG will convert original BILOG-MG
generated parameter file (*.PAR) in that folder, delete the first four lines
(title/comment information), remove standard error columns, and rename the files using the *.3PL
extension by following the 32x,2f12.6,12x,f12.6 format, which can be used
for running ITERLINK). PAR3PLMG will also retain 3 columns of a, b, c
parameters only in a 3PL model (from columns 4, 6, and 10 of the original BILOG-MG's *.PAR file),
and rename the file using the *.TXT extension (free-field format), which is
compatible with ParConversion.
- COVMG will convert original BILOG-MG
generated covariance file (*.COV) in that folder, and rename the file using the *.CVM extension (old BILOG format) for further analysis (e.g., ITERLINK)
- ParConversion (requires Microsoft .NET Framework through Windows update)
will convert original BILOG for DOS/Windows generated parameter files (*.PAR) in that folder, delete the first four lines (title/comment information) and subsequent alternating rows (standard errors), retain 3 columns of parameters a, b, c only in a 3PL model (from columns 4, 5, and 7 of original BILOG's *.PAR file), and rename the files using
*.TXT extension (free-field format).
- DFITD4 identifies DIF items, computes DTF, and when DTF is found, determines which DIF items, if any, should be removed to establish measurement equivalence. You may review DFITD4 instructions here.
Datasets and syntax
Sample raw data (raw.sav)
Sample syntax data (syn1.sps)
Sample example data (example.sav)
Complete dataset (dataset.zip)BILOG-MG sample
syntax and output files are available for download
here
Excel files
Other IRT programs
Additonal software listed below is available through Assessment Systems Corporation.
Programs developed by
Scientific Software International, Inc.
- BILOG estimates IRT Parameters for the 1-, 2-, or 3-parameter logistic model using marginal maximum-likelihood.
- BILOG-MG estimates IRT parameters for multiple groups, allowing detection of differential item functioning.
- MULTILOG performs multiple-category IRT analysis for polytomous IRT models.
- PARSCALE performs IRT Scaling, Item Analysis, and Scoring or Rating Scale Data.
- XCALIBRE performs Marginal maximum-likelihood IRT parameter estimation with small numbers of examinees or short tests, for the 2- and 3-parameter IRT model.
Programs developed by Educational Measurement Laboratory (also known as Statistical Laboratory for Educational and Psychological
Measurement) of University of Illinois at Urbana-Champaign.
- DETECT examines the signs and magnitudes of estimated conditional item pair covariances, given observed score on the remaining items.
- DIMTEST assesses lack of unidimensionality, operating in either a confirmatory mode.
- SIBTEST assesses single items for DIF or bundles of items for simultaneous DIF.
MicroFACT performs factor analysis for dichotomous and ordered polytomous response data.
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