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coldstart: Calibrating Generated Items Before Pretesting with Predicted Priors

Predicts Rasch item difficulty from item features (text embeddings from any model, template family, content metadata) by ridge regression (Hoerl and Kennard, 1970, <doi:10.1080/00401706.1970.10488634>) with honest out-of-sample uncertainty, uses the predictions as robust informative priors to calibrate new items from small pretest samples, in the spirit of using collateral information in calibration (Mislevy, Sheehan and Wingersky, 1993, <doi:10.1111/j.1745-3984.1993.tb00422.x>), plans the pretest sample size needed for a target precision, and diagnoses item families whose predictions cannot be trusted.

Version: 0.1.0
Depends: R (≥ 4.1)
Imports: stats
Suggests: knitr, markdown
Published: 2026-10-07
DOI: 10.32614/CRAN.package.coldstart (may not be active yet)
Author: Daniel Edi ORCID iD [aut, cre, cph]
Maintainer: Daniel Edi <danieledi2026 at gmail.com>
BugReports: https://github.com/edidatasolutions/coldstart/issues
License: MIT + file LICENSE
URL: https://github.com/edidatasolutions/coldstart, https://edidatasolutions.github.io/coldstart/
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: coldstart results

Documentation:

Reference manual: coldstart.html , coldstart.pdf
Vignettes: Calibrating generated items with predicted priors (source, R code)

Downloads:

Package source: coldstart_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: coldstart_0.1.0.zip
macOS binaries: r-release (arm64): coldstart_0.1.0.tgz, r-oldrel (arm64): coldstart_0.1.0.tgz, r-release (x86_64): coldstart_0.1.0.tgz, r-oldrel (x86_64): coldstart_0.1.0.tgz

Linking:

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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.