Package: BANOVA 1.2.1
BANOVA: Hierarchical Bayesian ANOVA Models
It covers several Bayesian Analysis of Variance (BANOVA) models used in analysis of experimental designs in which both within- and between- subjects factors are manipulated. They can be applied to data that are common in the behavioral and social sciences. The package includes: Hierarchical Bayes ANOVA models with normal response, t response, Binomial (Bernoulli) response, Poisson response, ordered multinomial response and multinomial response variables. All models accommodate unobserved heterogeneity by including a normal distribution of the parameters across individuals. Outputs of the package include tables of sums of squares, effect sizes and p-values, and tables of predictions, which are easily interpretable for behavioral and social researchers. The floodlight analysis and mediation analysis based on these models are also provided. BANOVA uses 'Stan' and 'JAGS' as the computational platform. References: Dong and Wedel (2017) <doi:10.18637/jss.v081.i09>; Wedel and Dong (2020) <doi:10.1002/jcpy.1111>.
Authors:
BANOVA_1.2.1.tar.gz
BANOVA_1.2.1.zip(r-4.5)BANOVA_1.2.1.zip(r-4.4)BANOVA_1.2.1.zip(r-4.3)
BANOVA_1.2.1.tgz(r-4.4-x86_64)BANOVA_1.2.1.tgz(r-4.4-arm64)BANOVA_1.2.1.tgz(r-4.3-x86_64)BANOVA_1.2.1.tgz(r-4.3-arm64)
BANOVA_1.2.1.tar.gz(r-4.5-noble)BANOVA_1.2.1.tar.gz(r-4.4-noble)
BANOVA_1.2.1.tgz(r-4.4-emscripten)BANOVA_1.2.1.tgz(r-4.3-emscripten)
BANOVA.pdf |BANOVA.html✨
BANOVA/json (API)
NEWS
# Install 'BANOVA' in R: |
install.packages('BANOVA', repos = c('https://banovaapp.r-universe.dev', 'https://cloud.r-project.org')) |
- bernlogtime - Data for analysis of effects of typicality, blur and color on gist perception of ads
- bpndata - Eye-movement data for analysis of print ad designs
- choicedata - Household Panel Data on Margarine Purchases
- colorad - Data for gist perception of advertising, study 1
- colorad2 - Data for gist perception of advertising, study 2
- condstudy - Data for the study of how brand attitudes were influenced by showing brands together with pleasant pictures
- condstudy_sub - A subset of data for the study of how brand attitudes were influenced by showing brands together with pleasant pictures
- goalstudy - Data for the study of the impact of the variety among means on motivation to pursue a goal
- ipadstudy - Data for the study of relation between Conspicuous, Brand Usage, Self-Brand Connection and attitudes toward the brand
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:ddc0fc39ec. Checks:OK: 1 NOTE: 8. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 07 2024 |
R-4.5-win-x86_64 | NOTE | Nov 07 2024 |
R-4.5-linux-x86_64 | NOTE | Nov 07 2024 |
R-4.4-win-x86_64 | NOTE | Nov 07 2024 |
R-4.4-mac-x86_64 | NOTE | Nov 07 2024 |
R-4.4-mac-aarch64 | NOTE | Nov 07 2024 |
R-4.3-win-x86_64 | NOTE | Nov 07 2024 |
R-4.3-mac-x86_64 | NOTE | Nov 07 2024 |
R-4.3-mac-aarch64 | NOTE | Nov 07 2024 |
Exports:BAnovaBANOVA.BernoulliBANOVA.BinomialBANOVA.buildBANOVA.floodlightBANOVA.mediationBANOVA.modelBANOVA.multi.mediationBANOVA.MultinomialBANOVA.NormalBANOVA.ordMultinomialBANOVA.PoissonBANOVA.runBANOVA.simpleBANOVA.Tconv.diagpairs.BANOVAtable.predictionstable.pvaluestrace.plot
Dependencies:abindbackportsBHcallrcheckmateclicodacolorspacedescdistributionalfansifarvergenericsggplot2gluegridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivpillarpkgbuildpkgconfigposteriorprocessxpsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelrjagsrlangrstanrunjagsscalesStanHeaderstensorAtibbleutf8vctrsviridisLitewithr