TY  - JOUR
A1  - Nicenboim, Bruno
A1  - Vasishth, Shravan
T1  - Statistical methods for linguistic research: Foundational Ideas-Part II
T2  - Language and linguistics compass
N2  - We provide an introductory review of Bayesian data analytical methods, with a focus on applications for linguistics, psychology, psycholinguistics, and cognitive science. The empirically oriented researcher will benefit from making Bayesian methods part of their statistical toolkit due to the many advantages of this framework, among them easier interpretation of results relative to research hypotheses and flexible model specification. We present an informal introduction to the foundational ideas behind Bayesian data analysis, using, as an example, a linear mixed models analysis of data from a typical psycholinguistics experiment. We discuss hypothesis testing using the Bayes factor and model selection using cross-validation. We close with some examples illustrating the flexibility of model specification in the Bayesian framework. Suggestions for further reading are also provided.
Y1  - 2016
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/44765
SN  - 1749-818X
VL  - 10
SP  - 591
EP  - 613
PB  - Wiley-Blackwell
CY  - Hoboken
ER  -