Package: NAP 1.1

Sandipan Pramanik

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.

Authors:Sandipan Pramanik [aut, cre], Valen E. Johnson [aut]

NAP_1.1.tar.gz
NAP_1.1.tar.gz(r-4.5-noble)NAP_1.1.tar.gz(r-4.4-noble)
NAP_1.1.tgz(r-4.4-emscripten)NAP_1.1.tgz(r-4.3-emscripten)
NAP.pdf |NAP.html✨
NAP/json (API)

# Install 'NAP' in R:
install.packages('NAP', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 119 downloads 17 mentions 43 exports 4 dependencies

Last updated 3 years agofrom:8122325557. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 27 2024
R-4.5-linuxOKOct 27 2024

Exports:fixedHajnal.onet_esfixedHajnal.onet_nfixedHajnal.onez_esfixedHajnal.onez_nfixedHajnal.twot_esfixedHajnal.twot_nfixedHajnal.twoz_esfixedHajnal.twoz_nfixedNAP.onet_esfixedNAP.onet_nfixedNAP.onez_esfixedNAP.onez_nfixedNAP.twot_esfixedNAP.twot_nfixedNAP.twoz_esfixedNAP.twoz_nHajnalBF_onetHajnalBF_onezHajnalBF_twotHajnalBF_twozimplement.SBFHajnal_onetimplement.SBFHajnal_onezimplement.SBFHajnal_twotimplement.SBFHajnal_twozimplement.SBFNAP_onetimplement.SBFNAP_onezimplement.SBFNAP_twotimplement.SBFNAP_twozmycombine.fixedmycombine.seq.onesamplemycombine.seq.twosampleNAPBF_onetNAPBF_onezNAPBF_twotNAPBF_twozSBFHajnal_onetSBFHajnal_onezSBFHajnal_twotSBFHajnal_twozSBFNAP_onetSBFNAP_onezSBFNAP_twotSBFNAP_twoz

Dependencies:codetoolsdoParallelforeachiterators

Readme and manuals

Help Manual

Help pageTopics
Non-Local Alternative Priors in PsychologyNAP-package NAP
Fixed-design one-sample t-tests using Hajnal's ratio for varied sample sizesfixedHajnal.onet_es
Fixed-design one-sample t-tests using Hajnal's ratio and a pre-fixed sample sizefixedHajnal.onet_n
Fixed-design one-sample z-tests using Hajnal's ratio for varied sample sizesfixedHajnal.onez_es
Fixed-design one-sample z-tests using Hajnal's ratio and a pre-fixed sample sizefixedHajnal.onez_n
Fixed-design two-sample t-tests with NAP for varied sample sizesfixedHajnal.twot_es
Fixed-design two-sample t-tests using Hajnal's ratio and a pre-fixed sample sizefixedHajnal.twot_n
Fixed-design two-sample z-tests with NAP for varied sample sizesfixedHajnal.twoz_es
Fixed-design two-sample z-tests using Hajnal's ratio and a pre-fixed sample sizefixedHajnal.twoz_n
Fixed-design one-sample t-tests with NAP for varied sample sizesfixedNAP.onet_es
Fixed-design one-sample t-tests with NAP and a pre-fixed sample sizefixedNAP.onet_n
Fixed-design one-sample z-tests with NAP for varied sample sizesfixedNAP.onez_es
Fixed-design one-sample z-tests with NAP and a pre-fixed sample sizefixedNAP.onez_n
Fixed-design two-sample t-tests with NAP for varied sample sizesfixedNAP.twot_es
Fixed-design two-sample t-tests with NAP and a pre-fixed sample sizefixedNAP.twot_n
Fixed-design two-sample z-tests with NAP for varied sample sizesfixedNAP.twoz_es
Fixed-design two-sample z-tests with NAP and a pre-fixed sample sizefixedNAP.twoz_n
Hajnal's ratio in one-sample t testsHajnalBF_onet
Hajnal's ratio in one-sample z testsHajnalBF_onez
Hajnal's ratio in two-sample t testsHajnalBF_twot
Hajnal's ratio in two-sample z testsHajnalBF_twoz
Implement Sequential Bayes Factor using the Hajnal's ratio for one-sample t-testsimplement.SBFHajnal_onet
Implement Sequential Bayes Factor using the Hajnal's ratio for one-sample z-testsimplement.SBFHajnal_onez
Implement Sequential Bayes Factor using the NAP for two-sample t-testsimplement.SBFHajnal_twot
Implement Sequential Bayes Factor using the NAP for two-sample z-testsimplement.SBFHajnal_twoz
Implement Sequential Bayes Factor using the NAP for one-sample t-testsimplement.SBFNAP_onet
Implement Sequential Bayes Factor using the NAP for one-sample z-testsimplement.SBFNAP_onez
Implement Sequential Bayes Factor using the NAP for two-sample t-testsimplement.SBFNAP_twot
Implement Sequential Bayes Factor using the NAP for two-sample z-testsimplement.SBFNAP_twoz
Helper functionmycombine.fixed
Helper functionmycombine.seq.onesample
Helper functionmycombine.seq.twosample
Bayes factor in favor of the NAP in one-sample t testsNAPBF_onet
Bayes factor in favor of the NAP in one-sample z testsNAPBF_onez
Bayes factor in favor of the NAP in two-sample t testsNAPBF_twot
Bayes factor in favor of the NAP in two-sample z testsNAPBF_twoz
Sequential Bayes Factor using the Hajnal's ratio for one-sample t-testsSBFHajnal_onet
Sequential Bayes Factor using the Hajnal's ratio for one-sample z-testsSBFHajnal_onez
Sequential Bayes Factor using the Hajnal's ratio for two-sample t-testsSBFHajnal_twot
Sequential Bayes Factor using the Hajnal's ratio for two-sample z-testsSBFHajnal_twoz
Sequential Bayes Factor using the NAP for one-sample t-testsSBFNAP_onet
Sequential Bayes Factor using the NAP for one-sample z-testsSBFNAP_onez
Sequential Bayes Factor using the NAP for two-sample t-testsSBFNAP_twot
Sequential Bayes Factor using the NAP for two-sample z-testsSBFNAP_twoz