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Volume 12: Number 2: Article 2
Empirical Evidence Against Decision Augmentation Theory
Y.H. Dobyns and R.D. Nelson, Princeton Engineering Anomalies Research,
Princeton University, Princeton, New Jersey 08544
A reference on the Decision Augmentation Theory (May et al.,
1995) includes a claim that certain data from the Princeton Engineering
Anomalies Research program support the DAT model while refuting bitwise
influence models at the 8.6s level. We present here an analysis of the
entire PEAR database published in Jahn et al. (1996), which shows that
the database as a whole is consistent with bitwise influence, and rejects
DAT at well over the 5s level in a linear regression test. The subset
of the data used by May et al. is examined in detail, and it
is shown that the 8.6s figure results from an erroneous analysis procedure.
Both the data set available to May, and the overall database, are strongly
inconsistent with DAT predictions while remaining consistent with a
bitwise influence model.
Keywords: human/machine interactions, Decision Augmentation Theory
FULL TEXT:
Empirical Evidence Against Decision Augmentation Theory
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