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MPTinR (version 1.11.0)

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.

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Version

Install

install.packages('MPTinR')

Monthly Downloads

472

Version

1.11.0

License

GPL (>= 2)

Maintainer

Henrik Singmann

Last Published

June 23rd, 2018

Functions in MPTinR (1.11.0)

get.mpt.fia

Convenient function to get FIA for MPT
gen.data

Generate or bootstrap data and get predictions from a model specified in a model file (or connection).
check.mpt

Check construction of MPT models.
MPTinR-package

MPTinR
d.broeder

Broeder & Schuetz (2009) Experiment 3
bmpt.fia

Compute FIA for MPTs
fit.mptinr

Fit cognitive models for categorical data using an objective function
fit.model

Fit cognitive models for categorical data using model files
fit.mpt.old

Function to fit MPT models (old)
make.eqn

Creates an EQN model file oir MDT data file
prepare.mpt.fia

Provides MATLAB command to get FIA
rb.fig1.data

Data to be used for the examples of MPTinR.
ROCs

Recognition memory ROCs used by Klauer & Kellen (2015)
fit.mpt

Function to fit MPT models
make.mpt.cf

Functions to transform MPT models.
select.mpt

Model Selection with MPTinR
prediction.plot

Plot observed versus predicted values for categorical data.