GithubHelp home page GithubHelp logo

treebugs's Introduction

CRAN_Status_Badge Workflow CRAN/METACRAN monthly downloads total downloads

TreeBUGS

TreeBUGS is an R package that facilitates using hierarchical multinomial processing tree (MPT) models that are often used in cognitive psychology (Erdfelder et al., 2009). Specifically, TreeBUGS implements the Bayesian estimation via MCMC sampling for the Beta-MPT (Smith & Batchelder, 2010), the latent-trait MPT model (Klauer, 2010), and standard (fixed-effects) MPT models.

General Approach of Using TreeBUGS

In the most simple user scenario, the following steps are required:

  1. Define path to existing MPT model file in .eqn format (cf. multiTree; Moshagen, 2010)
  2. Define path to data set with individual frequencies (.csv file: comma separated, rows=persons, columns=labeled categories)
  3. Call betaMPT or traitMPT (exact code in manual/vignette)
  4. Check convergence of MCMC chains
  5. Summarize and plot results using functions tailored to MPT models

These steps are explained in more detail in the package vignette, which can be opened in R by typing vignette("TreeBUGS").

Tutorial on MPT Modeling

A tutorial paper on multinomial processing tree models (including hierarchical model fitting with TreeBUGS) can be found here:

  • Schmidt, O., Erdfelder, E., & Heck, D. W. (2022). Tutorial on multinomial processing tree modeling: How to develop, test, and extend MPT models. PsyArXiv. https://psyarxiv.com/gh8md/

Installing TreeBUGS

TreeBUGS requires the software JAGS. To install the latest release of TreeBUGS from CRAN, type the following into the R console:

install.packages("TreeBUGS")

To install the latest developer version of TreeBUGS from GitHub, run:

### Dependencies:
install.packages(c("devtools", "coda", "runjags", "hypergeo", "testthat",
                   "rjags", "Rcpp", "RcppArmadillo", "logspline"))
devtools::install_github("danheck/TreeBUGS", build_vignettes = TRUE)

To compile C++ code, Windows and Mac require Rtools and Xcode Command Line Tools, respectively. Moreover, on Mac, it might be necessary to install the library gfortran manually by typing the following into the console (required to compile the package RcppArmadillo):

curl -O http://r.research.att.com/libs/gfortran-4.8.2-darwin13.tar.bz2
sudo tar fvxz gfortran-4.8.2-darwin13.tar.bz2 -C /

Citation

If you use TreeBUGS, please cite the software as follows:

  • Heck*, D. W., Arnold*, N. R., & Arnold, D. (2018). TreeBUGS: An R package for hierarchical multinomial-processing-tree modeling. Behavior Research Methods, 50, 264-284. https://doi.org/10.3758/s13428-017-0869-7

References

  • Batchelder, W. H., & Riefer, D. M. (1999). Theoretical and empirical review of multinomial process tree modeling. Psychonomic Bulletin & Review, 6, 57–86. https://doi.org/10.3758/BF03210812

  • Erdfelder, E., Auer, T.-S., Hilbig, B. E., Assfalg, A., Moshagen, M., & Nadarevic, L. (2009). Multinomial processing tree models: A review of the literature. Journal of Psychology, 217, 108–124. https://doi.org/10.1027/0044-3409.217.3.108

  • Klauer, K. C. (2010). Hierarchical multinomial processing tree models: A latent-trait approach. Psychometrika, 75, 70–98. https://doi.org/10.1007/s11336-009-9141-0

  • Matzke, D., Dolan, C. V., Batchelder, W. H., & Wagenmakers, E.-J. (2015). Bayesian estimation of multinomial processing tree models with heterogeneity in participants and items. Psychometrika, 80, 205–235. https://doi.org/10.1007/s11336-013-9374-9

  • Moshagen, M. (2010). multiTree: A computer program for the analysis of multinomial processing tree models. Behavior Research Methods, 42, 42–54. https://doi.org/10.3758/BRM.42.1.42

  • Smith, J. B., & Batchelder, W. H. (2010). Beta-MPT: Multinomial processing tree models for addressing individual differences. Journal of Mathematical Psychology, 54, 167–183. https://doi.org/10.1016/j.jmp.2009.06.007

treebugs's People

Contributors

danheck avatar mariusbarth avatar denis-arnold avatar crsh avatar soelderer avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.