MULTINOMIAL PROCESSING TREE MODELS

(MPT MODELS)

R code for fitting and testing the following types of multinomial processing tree models is available:

1. Different versions of the simplified conjoint recognition model of Stahl and Klauer (2008)

2. Different versions of the source monitoring model of Bayen et al. (2000)

The fitting and testing procedures comprise the following aspects:

• The method of estimation is maximum likelihood.

• Test statistics (Chi-square statistics, AIC, BIC) and model diagnostics (rank and condition number of the information matrix) are computed.

• If the model is properly estimated, confidence intervals of estimated parameters are computed from the observed information matrix (in two different way).

• Fixed, equality, and functional constraints of arbitrary complexity may be imposed on parameters.

• A documentation of the most important functions as well as working examples are available.

References

Bayen , U, Nakamura, G. V., Depuis, S. E., & Yang, C.-L. (2000). The use of schematic knowledge about sources in source monitoring. Memory & Cognition, 28, 480-500.

Stahl, C., & Klauer, K. C. (2008). A simplified conjoint recognition paradigm for the measurement of gist and verbatim memory. Journal of Experimental Psychology, Learning, Memory, & Cognition, 34, 570-586.

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