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help for ^bicdrop1^ - 1.0 - 6 Mar 2005
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Estimate the probability a model is more likely without each explanatory variable
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^bicdrop1^ [^, h^ighlight^(name)^ ]
Description
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^bicdrop1^ is a post-estimation command that uses the Bayesian Information Criterion
(BIC) to estimate the probability that the model would be more likely after dropping
one of the explanatory variables. The BIC was first proposed by Schwarz (1978) and
further developed by Raftery (1995).
It works after the following estimation commands:
^regress^, ^logistic^, ^logit^, ^ologit^, ^oprobit^, ^mlogit^, ^poisson^, ^nbreg^.
It also reports Akaike's AIC, an earlier measure of model likelihood, and BIC' (BIC
prime), an alternative measure proposed by Raftery for model comparison.
The command drops each explanatory variable from the model and reports the AIC, BIC
and BIC' associated with the resulting nested model and uses the differences between
the BIC for the reduced model and the full (original) model to calculate a
probability that the model is less likely if that explanatory (or independent)
variable is removed.
Note that the BIC difference is not a traditional hypothesis test, but a comparison
between the likelihood of two models: the original model and the model without one
of the variables. Nevertheless, the BIC difference is a more rigourous test of
whether the "true" model (i.e. the most likely model, given the data and the
likelihood form) contains the variable in question, especially where the traditional
significance tests are weak: where N is large; or where there are a lot of
explanatory variables (where k is large).
Acknowledgements
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This program was based on the approach taken by the command lrdrop1 (developed by
Z. Wang) and was suggested by Richard Williams of the University of Notre Dame.
The author is grateful for assistance and encouragement from Richard Williams of
the University of Notre Dame in the testing of this routine.
Options
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^h^ighlight(^"colour"^) highlights variables which are likely to be part of the model.
"colour" can be any of "^w^hite" "^g^reen" "^y^ellow" "^r^ed" or "^s^pecial"
Examples
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. ^regress cbecs09 cprcs03 cprcs05 ^
. ^bicdrop1^
Author: Paul Millar
www.ucalgary.ca/~pemillar/stata.htm
pemillar@@ucalgary.ca
See also:
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Online: help for @lrdrop1@, @fitstat@ (if installed)
References: Raftery, Adrian (1995) Bayesian Model Selection in Social Research
Sociological Methodology, Vol. 25, pp. 111-163.
Schwarz, Gideon (1978) Estimating the Dimension of a Model
The Annals of Statistics vol. 6, pp.461-64.