EMLAR 2022 tutorial on Bayesian methods
This article is originally published at https://vasishth-statistics.blogspot.com/
At EMLAR 2022 I will teach two sessions that will introduce Bayesian methods. Here is the abstract for the two sessions:
EMLAR 2022: An introduction to Bayesian data analysis
Taught by Shravan Vasishth (vasishth.github.io)
Session 1. 19 April 2022 (Zoom link will be provided)
Modern probabilistic programming languages like Stan (mc-stan.org)
have made Bayesian methods increasingly accessible to researchers
in linguistics and psychology. However, finding an entry point
into these methods is often difficult for researchers. In this
tutorial, I will provide an informal introduction to the
fundamental ideas behind Bayesian statistics, using examples
that illustrate applications to psycholinguistics.
I will also discuss some of the advantages of the Bayesian
approach over the standardly used frequentist paradigms:
uncertainty quantification, robust estimates through regularization,
the ability to incorporate expert and/or prior knowledge into
the data analysis, and the ability to flexibly define the
generative process and thereby to directly address the actual research
question (as opposed to a straw-man null hypothesis).
Suggestions for further reading will be provided. In this tutorial,
I presuppose that the audience is familiar with linear mixed models
(as used in R with the package lme4).
Session 2. 21 April 2022 (Zoom link will be provided)
This session presupposed that the participant has attended
Session 1. I will show some case studies using brms and Stan
code that will demonstrate the major applications of
Bayesian methods in psycholinguistics. I will reference/use some of
the material described in this online textbook (in progress):
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