binest: Estimation of Group Means and SDs from Binned Count Data

Education agencies often report school or district score distributions as the number of students scoring in each of several score ranges, or bins, separated by threshold scores, or cuts. The functions in the binest package translate those bin counts into estimates of the mean and standard deviation (SD). They do so using the heteroskedastic ordered probit (HETOP) model, which assumes that scores follow a normal distribution within each school or district, each of which has its own mean and SD. The binest package includes the fast_hetop() function, which fits the model much more quickly than previous implementations. The model is described by Reardon, Shear, Castellano and Ho (2017) <doi:10.3102/1076998616666279>; a Bayesian variant is described by Lockwood, Castellano and Shear (2018) <doi:10.3102/1076998618795124>.

Version:	0.3-1
Depends:	R (≥ 3.5.0)
Imports:	splines, stats, utils
Suggests:	knitr, rmarkdown, R2jags
Published:	2026-09-22
DOI:	10.32614/CRAN.package.binest
Author:	Paul T. von Hippel [aut, cre], David J. Hunter [aut], J.R. Lockwood [aut] (Original HETOP package author)
Maintainer:	Paul T. von Hippel <ph3828 at eid.utexas.edu>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
Materials:	README, NEWS
CRAN checks:	binest results

Documentation:

Reference manual:	binest.html , binest.pdf
Vignettes:	Estimating District Means and SDs from Binned Test Scores, with the binest package (source, R code)

Downloads:

Package source:	binest_0.3-1.tar.gz
Windows binaries:	r-devel: binest_0.2-1.zip, r-release: binest_0.2-1.zip, r-oldrel: binest_0.2-1.zip
macOS binaries:	r-release (arm64): binest_0.2-1.tgz, r-oldrel (arm64): binest_0.2-1.tgz, r-release (x86_64): binest_0.3-1.tgz, r-oldrel (x86_64): binest_0.3-0.tgz
Old sources:	binest archive

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