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NAP: Non-Local Alternative Priors in Psychology

Conducts Bayesian Hypothesis tests of a point null hypothesis against a two-sided alternative using Non-local Alternative Prior (NAP) for one- and two-sample z- and t-tests (Pramanik and Johnson, 2022). Under the alternative, the NAP is assumed on the standardized effects size in one-sample tests and on their differences in two-sample tests. The package considers two types of NAP densities: (1) the normal moment prior, and (2) the composite alternative. In fixed design tests, the functions calculate the Bayes factors and the expected weight of evidence for varied effect size and sample size. The package also provides a sequential testing framework using the Sequential Bayes Factor (SBF) design. The functions calculate the operating characteristics (OC) and the average sample number (ASN), and also conducts sequential tests for a sequentially observed data.

Version: 1.1
Imports: foreach, stats, utils, parallel, doParallel, graphics
Published: 2022-01-06
DOI: 10.32614/CRAN.package.NAP
Author: Sandipan Pramanik [aut, cre], Valen E. Johnson [aut]
Maintainer: Sandipan Pramanik <sandy at stat.tamu.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: NAP results

Documentation:

Reference manual: NAP.pdf

Downloads:

Package source: NAP_1.1.tar.gz
Windows binaries: r-devel: NAP_1.1.zip, r-release: NAP_1.1.zip, r-oldrel: NAP_1.1.zip
macOS binaries: r-release (arm64): NAP_1.1.tgz, r-oldrel (arm64): NAP_1.1.tgz, r-release (x86_64): NAP_1.1.tgz, r-oldrel (x86_64): NAP_1.1.tgz
Old sources: NAP archive

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.
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