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bayescogsci
Draft of book entitled An Introduction to Bayesian Data Analysis for Cognitive Science by Nicenboim, Schad, VasishthBayesLMMTutorial
Tutorial files to accompany Sorensen, Hohenstein, and Vasishth paper: http://www.ling.uni-potsdam.de/~vasishth/statistics/BayesLMMs.htmlIntroductionBayes
An introduction to Bayesian Data Analysis: A one-week courseMScStatisticsNotes
These are cheat sheets and notes I made as part of an MSc in Statistics, at the University of Sheffield, UK.Statistics-lecture-notes-Potsdam
Lecture notes from a statistics course I teach at PotsdamFreq_CogSci
Linear mixed models in Linguistics and Psychology: A Comprehensive IntroductionLM
lingpsych
Datasets and models included in the book "Linear Mixed Models for Linguistics and Psychology: A Comprehensive Introduction".IntroductionStatistics
An introduction to statistics from scratch. Prerequisites: Basic knowledge of R.IntroBayesSMLP2021
This is the course home page for Intro Bayes at SMLP 2021.VasishthNicenboimPart1
This repository contains the code and data that accompany the paper: Statistical methods for linguistic research: Foundational Ideas - Part I, by Shravan Vasishth and Bruno Nicenboim. Language and Linguistics Compass 10/8 (2016): 349β369, doi: 10.1111/lnc3.12201.NicenboimVasishthPart2
Code and data to accompany the article Statistical methods for linguistic research: Foundational Ideas - Part II, by Bruno Nicenboim and Shravan Vasishth. Language and Linguistics Compass, 2016. doi: 10.1111/lnc3.12207ESSLLI2015Vasishth_Week1
Material for ESSLLI 2015 (Week 1) course entitled Statistical methods for linguistic research: Foundational IdeasFoundationsOfMathematics
Lecture notes for the foundations of mathematics course taught in winter semester as part of the MSc in Cognitive Systems.FGME_Stan_2017
Repository for all lecture notes, code, and data relating to the Stan workshop at FGME 2017 in Tuebingen, Germany.MetaAnalysisJaegerEngelmannVasishth2017
Code and data to accompany paper by L.A. JΓ€ger, Engelmann, & Vasishth, 2017. Similarity-based interference in sentence comprehension: Literature review and Bayesian meta-analysis. Journal of Memory and Language. doi:10.1016/j.jml.2017.01.004StanJAGSexamples
Example code using Stan and JAGS for psycholinguistic dataIntroductionBDA
An Introductiion to Bayesian Data AnalysisStatisticsNotes
Everything I learnt in graduate school in statistics.jopbayes
Code and data for the Journal of Phonetics article entitled Bayesian data analysis in the phonetic sciences: A tutorial introductionESSLLI2015Vasishth_Week2
This repository contains the code and slides for the Statistics Methods course taught in Week 2 at ESSLLI 2015, Barcelona.SMLP2017
Summer School: Statistical Methods for Linguistics and Psychology, 2017, University of Potsdam, Germanysmlp2021
The Fifth Summer School in Statistical Methods for Linguistics and PsychologyIntro_Bayes_CogSci
An Introduction to Bayesian Data Analysis for Cognitive Science, Vasishth, Nicenboim, Schad, to appear, CRC PressVasishthLab
Psycholinguistic Data and Example Analyses from Vasishth Lab (Potsdam)smlp2024
The eight summer school on statistical methods for linguistics and psychologySMLP2018
Statistical Methods for Linguistics and Psychology, University of Potsdam, Germany, 10-14 September 2018EMLAR2022BayesTutorial
Materials for the EMLAR Bayes 1 and 2 tutorialsReproducibleWorkflows
Materials for MPI Leipzig workshop: https://www.cbs.mpg.de/events/23219/1413783SubsettingProblem
This repo contains the code relating to two blog posts at https://vasishth-statistics.blogspot.com/smlp2022
The website for SMLP 2022, 12-16 Sept 2022.BayesianLinearModeling
Lecture notes for the Bayesian linear modeling course taught in winter semester at the University of PotsdamMPILeipzig2019
Materials for the MPI Leipzig workshop and hands-on session on open scienceMScDissertationVasishth
Code+documentation and data to accompany my MSc dissertation in statistics from the School of Mathematics and Statistics, Sheffield, UK.manuscript_LogacevVasishth_CogSci_SMCM
Code + Data for the Logacev & Vasishth paper on underspecification and parallel processing. Proposes the SMCM as a task-dependent model of ambiguity resolution.MichiganLinguistics2020talk
slides and materials for Michigan talk on Feb 6, 2020vasishth.github.io
Shravan Vasishth's home pageVNEBTiCS2019
code for the draft of the paper by Vasishth et al: Computational models of retrieval processes in sentence processingagrmtreflexives
Large-sample Multilab replication attempt of Dillon et al 2013vasishth
Config files for my GitHub profile.EMLAR2021BayesTutorial
rstyleguidepotsdam
Style guide for R coding, University of PotsdamExpLing
Reproducible code and data for the chapter New Directions in Statistical Analysis for Experimental LinguisticsStatSigFilter
The Statistical Significance Filtersmlp2019
Statistical Methods for Linguistics and Psychology, University of Potsdam, GermanyRetrievalModels
Website to accomany book Sentence Comprehension as a Cognitive Processembraceuncertainty
Code and data to accompany the paper: Shravan Vasishth and Andrew Gelman. How to embrace variation and accept uncertainty in linguistic and psycholinguistic data analysis. Linguistics, 59:1311--1342, 2021. doi: https://doi.org/10.1515/ling-2019-0051VasishthEtAl2013PLoSONE
Data and code for the paper Shravan Vasishth, Zhong Chen, Qiang Li, and Gueilan Guo. Processing Chinese Relative Clauses: Evidence for the Subject-Relative Advantage. PLoS ONE, 8(10):1-14, 10 2013.Love Open Source and this site? Check out how you can help us