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Appendix G
The rescaled values are either 0 or positive. For example, the best model according to
AIC has , while inferior models have positive values that reflect how
much worse they are than the best model.
E To display , , and after a specification search, click on the
Specification Search toolbar.
E On the Current results tab of the Options dialog box, click Zero-based (min = 0).
Akaike Weights and Bayes Factors (Sum = 1)
E To obtain the following rescaling, select Akaike weights and Bayes factors (sum = 1) on
the Current results tab of the Options dialog box.
Each of these rescaled measures sums to 1 across models. The rescaling is performed
only after an exhaustive specification search. If a heuristic search is carried out or if a
positive value is specified for
Retain only the best ___ models, then the summation in
the denominator cannot be calculated, and rescaling is not performed. The are
called Akaike weights by Burnham and Anderson (1998). has the same
interpretation as . Within the Bayesian framework and under suitable
assumptions with equal prior probabilities for the models, the are approximate
posterior probabilities (Raftery, 1993, 1995).
AIC
0
0=
AIC
0
AIC
0
BCC
0
BIC
0
AIC
p
i
()
e
AIC
i()
2⁄–
e
AIC
m()
2⁄–
m
∑
----------------------------=
BCC
p
i
()
e
BCC
i()
2⁄–
e
BCC
m()
2⁄–
m
∑
-----------------------------=
BIC
p
i
()
e
BIC
i()
2⁄–
e
BIC
m()
2⁄–
m
∑
---------------------------=
AIC
p
i
()
BCC
p
i
()
AIC
p
i
()
BIC
p
i
()