Golden, R. M. (1997).
Causal network analysis validation using synthetic recall protocols.
Behavior Research Methods, Instruments & Computers, 29,
15-24.
ABSTRACT
Subjects read and recalled twelve short texts in a memory recall experiment.
The order in which subjects recalled the propositions in the text was recorded.
A causal network analysis of each text was then done in order to determine
how the propositions in each text were causally related. In addition, an
episodic memory network analysis of each text was done in order to represent
the original order of propositions presented to each subject in the experiment.
The human text recall data was then analyzed using a new statistical methodology
known as the Temporal Markov Field (TMF) approach
which makes explicit probabilistic
predictions about the ordering of propositions in human
subject recall protocols
in terms of the causal network and episodic memory network
analysis of a given text.
Samples from the TMF probability model were then used to
generate synthetic protocol
data using half of the human subject data.
Statistics computed with respect to the
remaining half of the human subject data and the
synthesized protocol data were
qualitatively
similar in many respects.
Relevant discrepancies between the human protocol data
and synthesized protocol data were also identified.
Semi-final post script draft (possibly missing figures)
Golden's Text Comprehension and Memory Publications