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Efficient Designs for Judgment Analysis. Edition No. 1
VDM Publishing House, Aug 2008, Pages: 248
In formulating a public policy, judgment analysis
enables policy makers to assess and accommodate the
relative importance of differing viewpoints and
concerns of competing actors as an analytic decision
aid. Among the important constraints that prevent
judgment analysis from being widely applied to the
policy formulation process is a methodological
limitation inherent in judgment analysis: It requires
too many scenarios to be judged in a single judgment
task.
Addressing this issue, this dissertation implemented
two efficient design concepts - efficient plausible
design and augmented representative design -
suggested by McClelland (1999) as alternative design
frameworks for judgment analysis that balance two
conflicting principles: the principles of
representative design and statistical efficiency. It
also sought to derive a generalizable rule about the
minimum number of cases needed to arrive at reliable
conclusions about a judgment policy given the
judgment task. Additionally, it tested the
applicability of the bootstrap analysis as an
alternative method to estimate the stability of the
coefficients modeled for a judgment policy given the
limited number of observations.
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