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vasishth/embraceuncertainty

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vasishth/embraceuncertainty

vasishth

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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-2019-0051

bayescogsci

Draft of book entitled An Introduction to Bayesian Data Analysis for Cognitive Science by Nicenboim, Schad, Vasishth

BayesLMMTutorial

Tutorial files to accompany Sorensen, Hohenstein, and Vasishth paper: http://www.ling.uni-potsdam.de/~vasishth/statistics/BayesLMMs.html

IntroductionBayes

An introduction to Bayesian Data Analysis: A one-week course

MScStatisticsNotes

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 Potsdam

Freq_CogSci

Linear mixed models in Linguistics and Psychology: A Comprehensive Introduction

LM

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): 349–369, 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/lnc3.12207

ESSLLI2015Vasishth_Week1

Material for ESSLLI 2015 (Week 1) course entitled Statistical methods for linguistic research: Foundational Ideas

FoundationsOfMathematics

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. Jäger, 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.2017.01.004

StanJAGSexamples

Example code using Stan and JAGS for psycholinguistic data

IntroductionBDA

An Introductiion to Bayesian Data Analysis

StatisticsNotes

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 introduction

ESSLLI2015Vasishth_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, Germany

smlp2021

The Fifth Summer School in Statistical Methods for Linguistics and Psychology

Intro_Bayes_CogSci

An Introduction to Bayesian Data Analysis for Cognitive Science, Vasishth, Nicenboim, Schad, to appear, CRC Press

VasishthLab

Psycholinguistic Data and Example Analyses from Vasishth Lab (Potsdam)

smlp2024

The eight summer school on statistical methods for linguistics and psychology

SMLP2018

Statistical Methods for Linguistics and Psychology, University of Potsdam, Germany, 10-14 September 2018

EMLAR2022BayesTutorial

Materials for the EMLAR Bayes 1 and 2 tutorials

ReproducibleWorkflows

Materials for MPI Leipzig workshop: https://www.cbs.mpg.de/events/23219/1413783

SubsettingProblem

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 Potsdam

powerpose

Reanalysis of Carney, Cuddy, and Yap 2010 data on power posing.

MPILeipzig2019

Materials for the MPI Leipzig workshop and hands-on session on open science

MScDissertationVasishth

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, 2020

vasishth.github.io

Shravan Vasishth's home page

VNEBTiCS2019

code for the draft of the paper by Vasishth et al: Computational models of retrieval processes in sentence processing

agrmtreflexives

Large-sample Multilab replication attempt of Dillon et al 2013

vasishth

Config files for my GitHub profile.

EMLAR2021BayesTutorial

rstyleguidepotsdam

Style guide for R coding, University of Potsdam

ExpLing

Reproducible code and data for the chapter New Directions in Statistical Analysis for Experimental Linguistics

StatSigFilter

The Statistical Significance Filter

smlp2019

Statistical Methods for Linguistics and Psychology, University of Potsdam, Germany

RetrievalModels

Website to accomany book Sentence Comprehension as a Cognitive Process

VasishthEtAl2013PLoSONE

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.