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RoBTT  

Robust Bayesian T-Test
View on CRAN: Click here


Download and install RoBTT package within the R console
Install from CRAN:
install.packages("RoBTT")

Install from Github:
library("remotes")
install_github("cran/RoBTT")

Install by package version:
library("remotes")
install_version("RoBTT", "1.3.1")



Attach the package and use:
library("RoBTT")
Maintained by
František Bartoš
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-09-20
Latest Update: 2024-11-10
Description:
An implementation of Bayesian model-averaged t-test that allows users to draw inference about the presence vs absence of the effect, heterogeneity of variances, and outliers. The 'RoBTT' packages estimates model ensembles of models created as a combination of the competing hypotheses and uses Bayesian model-averaging to combine the models using posterior model probabilities. Users can obtain the model-averaged posterior distributions and inclusion Bayes factors which account for the uncertainty in the data generating process (Maier et al., 2022, ). Users can define a wide range of informative priors for all parameters of interest. The package provides convenient functions for summary, visualizations, and fit diagnostics.
How to cite:
František Bartoš (2022). RoBTT: Robust Bayesian T-Test. R package version 1.3.1, https://cran.r-project.org/web/packages/RoBTT. Accessed 07 Oct. 2026.
Previous versions and publish date:
(2026-07-09 08:23), 1.0.0 (2022-09-20 10:06), 1.0.1 (2023-03-13 17:50), 1.0.2 (2023-03-30 10:20), 1.0.3 (2023-03-30 12:40), 1.1.0 (2023-05-30 16:00), 1.2.0 (2023-06-26 10:30), 1.2.1 (2023-09-20 10:30), 1.3.0 (2024-04-05 01:43)
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Complete documentation for RoBTT
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