MPTmultiverse is an R package that provides functions for a multiverse analysis of multinomial processing tree (MPT) models. Note that the package is currently work in progress and should be considered alpha. If you experience problems, open an issue.
To install MPTmultiverse
, make sure you already installed the devtools
package via install.packages("devtools")
. Moreover, you also need a to have JAGS installed: Go to http://mcmc-jags.sourceforge.net/ for instructions on how to install JAGS on your machine.
If these prerequisites are met, type devtools::install_github("mpt-network/MPTmultiverse")
in your R console to install MPTmultiverse
together with all required packages that it depends on. To make sure that you are using the latest versions of all packages, you should also run update.packages(ask = FALSE)
.
- Create a new folder that contains the following three files
(cf. the subfolder
vignettes/
):- The MPT model in the
.eqn
-format- The model should be parameterized including all equality constraints.
- To encode fixed parameters (e.g., g=.50), replace the parameter in the eqn-file by constants.
- The data with individual frequencies as a
.csv
-file - The file
analysis.rmd
(copied from thevignettes
subfolder).
- The MPT model in the
- Adjust the input options in
analysis.rmd
in the section "MPT model definition & Data". You have to specify the correct file names and the names of the columns in your data that contain a subject identifier and between-subjects conditions. - Optionally, set some options (e.g., the number of bootstrap samples) via
mpt_options()
- Run the analysis script (e.g., by knitting the .rmd file).
- For the Bayesian models with "no-pooling" and "complete-pooling", no additional
MCMC samples are drawn to achieve the desired level of convergence (e.g.,
Rhat < 1.05
). This might be addressed in future versions of TreeBUGS. As a remedy, the number of MCMC iterations can be increased a priori (viampt_options()
).
All code in this repository is released under the GPL v2 or later license. All non-code materials is released under the CC-BY-SA license.