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robtt

RoBTT R package for estimating robust Bayesian t-test

https://github.com/fbartos/robtt

Science Score: 26.0%

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    Low similarity (16.2%) to scientific vocabulary

Keywords

bayesian model-averaging outliers t-test

Keywords from Contributors

jasp meta-analysis
Last synced: 6 months ago · JSON representation

Repository

RoBTT R package for estimating robust Bayesian t-test

Basic Info
  • Host: GitHub
  • Owner: FBartos
  • Language: R
  • Default Branch: master
  • Homepage:
  • Size: 792 MB
Statistics
  • Stars: 3
  • Watchers: 2
  • Forks: 1
  • Open Issues: 0
  • Releases: 8
Topics
bayesian model-averaging outliers t-test
Created almost 5 years ago · Last pushed over 1 year ago
Metadata Files
Readme Changelog

README.Rmd 

---
title:        "README"
bibliography: inst/REFERENCES.bib
csl:          inst/apa.csl
output:       github_document
---


```{r include = FALSE, eval = FALSE}

```
```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment  = "#>",
  fig.path = "man/figures/README-",
  dev      = "png"
)
if(.Platform$OS.type == "windows"){
  knitr::opts_chunk$set(dev.args = list(type = "cairo"))
}
```


[![CRAN status](https://www.r-pkg.org/badges/version/RoBTT)](https://CRAN.R-project.org/package=RoBTT)




# Robust Bayesian T-Test (RoBTT)

This package provides an implementation of Bayesian model-averaged t-tests 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. User can define a wide range of informative priors for all parameters of interest. The package provides convenient functions for summary, visualizations, and fit diagnostics.

See our manuscripts for more information about the methodology:

  - @maier2022bayesian introduces a robust Bayesian t-test that model-averages over normal and t-distributions to account for the uncertainty about potential outliers,
  - @godmann2024how introduces a truncated Bayesian t-test that accounts for outlier exclusion when estimating the models.

We also prepared vignettes that illustrate functionality of the package:

 - [Introduction to RoBTT](https://fbartos.github.io/RoBTT/articles/Introduction_to_RoBTT.html)
 - [Truncated T-Tests](https://fbartos.github.io/RoBTT/articles/Truncated_t_test.html)


## Installation

The release version can be installed from CRAN:
``` r
install.packages("RoBTT")
```
and the development version of the package can be installed from GitHub:

``` r
devtools::install_github("FBartos/RoBTT")
```


### References

Owner

  • Name: František Bartoš
  • Login: FBartos
  • Kind: user

A (Psych Methods) PhD Candidate at the University of Amsterdam. I’m interested in meta-analyses, publication bias, replicability, and Bayesian inference.

GitHub Events

Total
  • Release event: 1
  • Delete event: 1
  • Push event: 7
  • Pull request event: 1
  • Create event: 1
Last Year
  • Release event: 1
  • Delete event: 1
  • Push event: 7
  • Pull request event: 1
  • Create event: 1

Committers

Last synced: over 1 year ago

All Time
  • Total Commits: 62
  • Total Committers: 4
  • Avg Commits per committer: 15.5
  • Development Distribution Score (DDS): 0.226
Past Year
  • Commits: 4
  • Committers: 2
  • Avg Commits per committer: 2.0
  • Development Distribution Score (DDS): 0.25
Top Committers
Name Email Commits
Frantisek Bartos f****6@g****m 48
FBartos 3****s 10
Andrew Johnson a****n@a****m 3
MaxMaier42 4****2 1
Committer Domains (Top 20 + Academic)
arjohnsonau.com: 1

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 1
  • Total pull requests: 10
  • Average time to close issues: about 1 month
  • Average time to close pull requests: about 1 month
  • Total issue authors: 1
  • Total pull request authors: 3
  • Average comments per issue: 1.0
  • Average comments per pull request: 1.5
  • Merged pull requests: 10
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: about 2 months
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • Beliavsky (1)
Pull Request Authors
  • FBartos (8)
  • andrjohns (3)
  • hrgodmann (2)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 598 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 9
  • Total maintainers: 1
cran.r-project.org: RoBTT

Robust Bayesian T-Test

  • Versions: 9
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 598 Last month
Rankings
Forks count: 21.0%
Dependent repos count: 24.0%
Average: 25.1%
Stargazers count: 25.5%
Downloads: 26.5%
Dependent packages count: 28.8%
Maintainers (1)
f.bartos96@gmail.com
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • Rcpp >= 0.12.19 depends
  • rstan >= 2.18.1 imports
.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v3 composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/pkgdown.yaml actions
  • actions/cache v2 composite
  • actions/checkout v2 composite
  • r-lib/actions/setup-pandoc v1 composite
  • r-lib/actions/setup-r v1 composite
.github/workflows/test-coverage.yaml actions
  • actions/checkout v3 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite