RoBTT: Robust Bayesian t-test

RoBTT: Bayesian model-averaged t-test extends the Bayesian t-test by incorporating inference about heterogeneity of variances and outliers.

User guide

See Maier et al. (2022) for details regarding the RoBTT methodology.

More details regarding customization of the Bayesian model-averaged t-test are provided in Introduction to RoBTT vignette. Please, use the "Issues" section in the GitHub repository to ask any further questions.

References

Maier M, Bartoš F, Quintana DS, van den Bergh D, Marsman M, Ly A, Wagenmakers E (2022). “Model-averaged Bayesian t-tests.” doi:10.31234/osf.io/d5zwc , PsyArxiv Preprint.

See also

Useful links:

• https://fbartos.github.io/RoBTT/

• Report bugs at https://github.com/FBartos/RoBTT/issues

Author

František Bartoš f.bartos96@gmail.com