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When samples contain missing data, are small, or are suspected of bias, estimation of scale reliability may not be trustworthy. A recommended solution for this common problem has been Bayesian model estimation. Bayesian methods rely on user specified information from historical data or researcher intuition to more accurately estimate the parameters. This package provides a user friendly interface for estimating test reliability. Here, reliability is modeled as a beta distributed random variable with shape parameters alpha=true score variance and beta=error variance (Tanzer & Harlow, 2020) <doi:10.1080/00273171.2020.1854082>.
Version: | 0.1.2 |
Depends: | MCMCpack, GPArotation, TeachingDemos, blavaan, blme |
Imports: | MASS, rstan |
Published: | 2021-01-26 |
DOI: | 10.32614/CRAN.package.brxx |
Author: | Joshua Ray Tanzer |
Maintainer: | Joshua Ray Tanzer <jtanzer at lifespan.org> |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
Materials: | README NEWS |
In views: | MissingData |
CRAN checks: | brxx results |
Reference manual: | brxx.pdf |
Package source: | brxx_0.1.2.tar.gz |
Windows binaries: | r-devel: brxx_0.1.2.zip, r-release: brxx_0.1.2.zip, r-oldrel: brxx_0.1.2.zip |
macOS binaries: | r-release (arm64): brxx_0.1.2.tgz, r-oldrel (arm64): brxx_0.1.2.tgz, r-release (x86_64): brxx_0.1.2.tgz, r-oldrel (x86_64): brxx_0.1.2.tgz |
Old sources: | brxx archive |
Please use the canonical form https://CRAN.R-project.org/package=brxx 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.
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