| MPTinR-package {MPTinR} | R Documentation |
Analyze Multinomial Processing Tree Models
Description
Provides a user-friendly way for the analysis of multinomial processing tree (MPT) models (e.g., Riefer, D. M., and Batchelder, W. H. [1988]. Multinomial modeling and the measurement of cognitive processes. Psychological Review, 95, 318-339) for single and multiple datasets. The main functions perform model fitting and model selection. Model selection can be done using AIC, BIC, or the Fisher Information Approximation (FIA) a measure based on the Minimum Description Length (MDL) framework. The model and restrictions can be specified in external files or within an R script in an intuitive syntax or using the context-free language for MPTs. The 'classical' .EQN file format for model files is also supported. Besides MPTs, this package can fit a wide variety of other cognitive models such as SDT models (see fit.model). It also supports multicore fitting and FIA calculation (using the snowfall package), can generate or bootstrap data for simulations, and plot predicted versus observed data.
Details
The DESCRIPTION file:
| Package: | MPTinR |
| Type: | Package |
| Title: | Analyze Multinomial Processing Tree Models |
| Version: | 1.14.1 |
| Authors@R: | c(person("Henrik", "Singmann", role = c("aut", "cre"), email = "singmann@gmail.com"), person("David", "Kellen", role = "aut"), person("Quentin", "Gronau", role = "aut"), person("Christian", "Mueller", role = "ctb"), person("Akhil S", "Bhel", role = "ctb")) |
| Description: | Provides a user-friendly way for the analysis of multinomial processing tree (MPT) models (e.g., Riefer, D. M., and Batchelder, W. H. [1988]. Multinomial modeling and the measurement of cognitive processes. Psychological Review, 95, 318-339) for single and multiple datasets. The main functions perform model fitting and model selection. Model selection can be done using AIC, BIC, or the Fisher Information Approximation (FIA) a measure based on the Minimum Description Length (MDL) framework. The model and restrictions can be specified in external files or within an R script in an intuitive syntax or using the context-free language for MPTs. The 'classical' .EQN file format for model files is also supported. Besides MPTs, this package can fit a wide variety of other cognitive models such as SDT models (see fit.model). It also supports multicore fitting and FIA calculation (using the snowfall package), can generate or bootstrap data for simulations, and plot predicted versus observed data. |
| License: | GPL (>= 2) |
| Depends: | R (>= 2.15.1) |
| Imports: | numDeriv, Brobdingnag, Rcpp, stats, utils |
| Suggests: | snowfall (>= 1.84), knitr |
| LinkingTo: | Rcpp, RcppEigen |
| LazyLoad: | yes |
| ByteCompile: | yes |
| VignetteBuilder: | knitr |
| NeedsCompilation: | yes |
| Packaged: | 2021-07-13 10:44:49 UTC; singm |
| Author: | Henrik Singmann [aut, cre], David Kellen [aut], Quentin Gronau [aut], Christian Mueller [ctb], Akhil S Bhel [ctb] |
| Maintainer: | Henrik Singmann <singmann@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2021-07-13 11:30:02 UTC |
Index of help topics:
MPTinR-package Analyze Multinomial Processing Tree Models
bmpt.fia Compute FIA for MPTs
check.mpt Check construction of MPT models.
d.broeder Broeder & Schuetz (2009) Experiment 3
fit.model Fit cognitive models for categorical data using
model files
fit.mpt Function to fit MPT models
fit.mpt.old Function to fit MPT models (old)
fit.mptinr Fit cognitive models for categorical data using
an objective function
gen.data Generate or bootstrap data and get predictions
from a model specified in a model file (or
connection).
get.mpt.fia Convenient function to get FIA for MPT
make.eqn Creates an EQN model file oir MDT data file
make.mpt.cf Functions to transform MPT models.
prediction.plot Plot observed versus predicted values for
categorical data.
prepare.mpt.fia Provides MATLAB command to get FIA
rb.fig1.data Data to be used for the examples of MPTinR.
roc6 Recognition memory ROCs used by Klauer & Kellen
(2015)
select.mpt Model Selection with MPTinR
Further information is available in the following vignettes:
mptinr_introduction | MPTinR: Analysis of Multinomial Processing Tree Models (source, pdf) |
To fit MPT Models use fit.mpt, to fit other models use fit.model or fit.mptinr (which is called by the other two functions).
For model selection use select.mpt.
A helper function for writing model files is check.mpt
References
Riefer, D. M., & Batchelder, W. H. (1988). Multinomial modeling and the measurement of cognitive processes. Psychological Review, 95, 318-339
Singmann, H., & Kellen, D. (2013). MPTinR: Analysis of multinomial processing tree models in R. Behavior Research Methods, 45(2), 560-575. doi:10.3758/s13428-012-0259-0