miebl: Performance Criteria Modeler for Discrete Trial Training

Provides a tool for computing probabilities and other quantities that are relevant in selecting performance criteria for discrete trial training. The main function, miebl(), computes Bayesian and frequentist probabilities and bounds for each of n possible performance criterion choices when attempting to determine a student's true mastery level by counting their number of successful attempts at displaying learning among n trials. The reporting function miebl_re() takes output from miebl() and prepares it into a brief report for a specific criterion. miebl_cp() combines 2 to 5 distributions of true mastery level given performance criterion in one plot for comparison. Ramos (2025) <doi:10.1007/s40617-025-01058-9>.

Version:	0.1.0
Depends:	R (≥ 2.10)
Imports:	graphics, stats
Published:	2025-04-25
DOI:	10.32614/CRAN.package.miebl
Author:	Mark Ramos [aut, cre, cph]
Maintainer:	Mark Ramos <mlr6219 at psu.edu>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	miebl results

Documentation:

Reference manual:

miebl.pdf

Downloads:

Package source:	miebl_0.1.0.tar.gz
Windows binaries:	r-devel: not available, r-release: miebl_0.1.0.zip, r-oldrel: miebl_0.1.0.zip
macOS binaries:	r-release (arm64): miebl_0.1.0.tgz, r-oldrel (arm64): miebl_0.1.0.tgz, r-release (x86_64): miebl_0.1.0.tgz, r-oldrel (x86_64): miebl_0.1.0.tgz

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