Here is a link to the folder containing video recordings of Stefano’s presentation and related R scripts.
Below are links to some extra resources on Bayesian data analysis, with recommendations from Stefano:
- The overview by Etz et al., How to become a Bayesian in eight easy steps: An annotated reading list, is a good place to start from if you want to learn more about Bayesian statistics and inference. https://link.springer.com/article/10.3758/s13423-017-1317-5
- Statistical (Re)thinking by Richard McElreath (https://xcelab.net/rm/statistical-rethinking/) is an excellent introduction for absolute beginners, by Richard McElreath, which covers a wide variety of linear models. It focusses on Bayesian inference and how this framework can help us directly answer research questions, assess evidence for different hypothesis, and quantify uncertainty. If you are familiar with the tidyverse, the code from the Statistical (Re)thinking book has been translated into tidyverse by Solomon Kurz, and it can be accessed here: https://bookdown.org/content/4857/
- Another book: An Introduction to Bayesian Data Analysis for Cognitive Science https://vasishth.github.io/bayescogsci/book/ (can be a bit technical)
- Tutorials:
– https://doi.org/10.1016/j.wocn.2018.07.008
– https://doi.org/10.1044/2018_JSLHR-S-18-0006
– Analysis of rating scales: A pervasive problem in bilingualism research and a solution with Bayesian ordinal models: https://www.cambridge.org/core/journals/bilingualism-language-and-cognition/article/abs/analysis-of-rating-scales-a-pervasive-problem-in-bilingualism-research-and-a-solution-with-bayesian-ordinal-models/4FC31D90EE220CBD488CB982D52B7D86#
– https://compass.onlinelibrary.wiley.com/doi/full/10.1111/lnc3.12439
- Learn Bayesian Analysis for Speech Sciences Workshop:
– Main site: https://learnb4ss.github.io/
– Materials: https://learnb4ss.github.io/learnB4SS/
– Videos: https://youtube.com/channel/UC7A52Cd3yl7zqLmsb_ucdog