Individual Differences in Memory Retention
The R & JAGS script we used today to discuss ch. 10 “Individual Differences in Memory Retention” of Lee & Wagenmakers (“Bayesian Cognitive Modeling: A Practical Course”, to appear) is available here: ch-10-LW.r. As we mentioned during the meeting, this chapter is an intro to random-effects models (random effects by …
read moreGeneralized Context Model
Ryan Bennett presented ch. 14 “Generalized Context Model” of Lee & Wagenmakers (“Bayesian Cognitive Modeling: A Practical Course”, to appear) on March 15. The R script discussed in class is available here: GCM-code.R. You can find the required data file “KruschkeData.mat” in the “Code.zip” file available on …
read moreSignal Detection Theory
Bootstrapping in a language of thought
Karl DeVries presented ch. 2 (“Bootstrapping in a language of thought: a formal model of conceptual change in number word learning”) of Steve Piantadosi’s 2011 dissertation (Learning and the language of thought) on March 8.
Steve is currently developing LOTlib, a python library to model learning complex concepts as …
read moreHeuristic Decision-Making
Jennifer Sawyer presented ch. 13 “Heuristic Decision-Making” of Lee & Wagenmakers (“Bayesian Cognitive Modeling: A Practical Course”, to appear) on March 6. The two Take-The-Best (TTB) scripts and BUGS models are available here: TakeTheBest-1.R, TakeTheBest-2.R, TakeTheBest-1.txt, TakeTheBest-2.txt. The WinBUGS plots and summary for TTB 2 are available …
read moreLicensing sentence-internal readings in English
As a follow-up to our intro to ordinal probit regression, the Feb. 28 class discussed an experiment investigating the semantics of sentence-internal readings in English (joint research by Jakub Dotlacil and Adrian Brasoveanu). The paper reporting the results of the acceptability-judgment experiment and its consequences for the semantics of sentence-internal …
read moreLaLoCo mailing list
Generalized linear (mixed) models etc.
The last 2 scripts introduce generalized linear (mixed) models and some extensions:
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First script: bayes-winbugs-jags-5.r; contents:
- generalized linear models
- Poisson “t-test” (simulated data, R analysis, WinBUGS / JAGS analysis)
- binomial “t-test” (simulated data, R analysis, WinBUGS / JAGS analysis)
- binomial ANCOVA (simulated data, R analysis, WinBUGS / JAGS analysis)
- binomial GLMM (simulated …
Linear and linear mixed-effects models in R and WinBUGS / JAGS
Plan for the Feb. 7, Feb. 9 and probably Feb. 14 classes (again, feel free to bring your laptops to class and work through the scripts on your own as we go through them in class):
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First script: bayes-winbugs-jags-3.r; contents: - simple linear regression (simulated data, R analysis, WinBUGS / JAGS …
Intro to WinBUGS / JAGS
Plan for the Jan. 31 & Feb. 2 classes; feel free to bring your laptops to class and work through the scripts on your own as we go through them in class:
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First script: bayes-winbugs-jags-1.r; contents:
- the mean model: simulated data, R analysis, WinBUGS / JAGS analysis
- the structure of WinBUGS …