PROCESSING TREE MODELS
for fitting and testing the following types of multinomial processing
tree models is available:
versions of the simplified conjoint recognition model of Stahl and
Different versions of
the source monitoring model of Bayen et al. (2000)
The fitting and testing
procedures comprise the following aspects:
method of estimation is maximum likelihood.
(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).
equality, and functional constraints of arbitrary complexity may be
imposed on parameters.
of the most important functions as well as working examples are
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,
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.