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PP: Person Parameter Estimation

Estimation of person parameters (abilities) for the 1, 2, 3 and 4 parameter logistic model, the (generalized) partial credit model and tests that mix dichotomous and polytomous items, under the assumption that the item parameters are known and fixed: maximum likelihood, weighted likelihood (Warm, 1989 <doi:10.1007/BF02294627>), maximum and expected a posteriori and robust estimation (Schuster and Yuan, 2011 <doi:10.3102/1076998610396890>). Further features are jackknife estimates (Wainer and Wright, 1980 <doi:10.1007/BF02293910>), plausible values, the person fit statistics lz, lz* (Snijders, 2001 <doi:10.1007/BF02294437>), infit and outfit, and the simulation of response data. Models fitted with the 'eRm' package can be passed on directly. The package is useful, e.g., when items of an item bank are given to a new sample of persons.

Version: 1.0.0
Depends: R (≥ 4.0)
Imports: graphics, Rcpp (≥ 1.0.0), stats, tinyplot (≥ 0.8.0), utils
LinkingTo: Rcpp
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown, eRm
Published: 2026-10-14
DOI: 10.32614/CRAN.package.PP
Author: Manuel Reif [cre, aut], Jan Steinfeld ORCID iD [aut]
Maintainer: Manuel Reif <manuel.reif at gmail.com>
BugReports: https://github.com/manuelreif/PP/issues
License: GPL-3
URL: https://github.com/manuelreif/PP, https://manuelreif.github.io/PP/
NeedsCompilation: yes
Citation: PP citation info
Materials: NEWS
In views: Psychometrics
CRAN checks: PP results

Documentation:

Reference manual: PP.html , PP.pdf
Vignettes: Person fit with PP (source, R code)
Getting started with PP (source, R code)
Person assessment with PPass, also for eRm models (source, R code)

Downloads:

Package source: PP_1.0.0.tar.gz
Windows binaries: r-devel: PP_0.6.4-1.zip, r-release: PP_0.6.4-1.zip, r-oldrel: PP_0.6.4-1.zip
macOS binaries: r-release (arm64): PP_0.6.4-1.tgz, r-oldrel (arm64): PP_0.6.4-1.tgz, r-release (x86_64): PP_0.6.4-1.tgz, r-oldrel (x86_64): PP_0.6.4-1.tgz
Old sources: PP archive

Reverse dependencies:

Reverse imports: mstDIF

Linking:

Please use the canonical form https://CRAN.R-project.org/package=PP to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.