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Note: This FAQ is for users of Stata 6, an older version of Stata. It is not relevant for more recent versions; see [R] zip.

Stata 6: How do I interpret the Vuong statistic of a test between a negative binomial and a zero-inflated negative binomial model for count data?

Stata 6: How do I interpret the Vuong statistic of a test between a Poisson and a zero-inflated Poisson model for count data?

Title   Stata 6: Interpreting the Vuong statistic of a test between two count data models
Author David M. Drukker, StataCorp
Date February 2000

Vuong (1989) developed some general tests of nonnested models. Greene (1994) adapts one of these tests to the cases ZIP vs. Poisson and zero-inflated negative binomial vs. negative binomial models. This test has been implemented in Stata (see zip and zinb). As described in Long (1997), this statistic has a standard normal distribution with large positive values favoring the zero-inflated model and with large negative values favoring the nonzero-inflated version. Values close to zero in absolute value favor neither model.

References

Greene, W. H. 1994.
Accounting for Excess Zeros and Sample Selection in Poisson and Negative Binomial Regression Models. Working paper, Stern School of Business, NYU EC-94-10.
Long, J. S. 1997.
Regression Models for Categorical and Limited Dependent Variables. Thousand Oaks, CA: Sage Publications.
Vuong, Q. H. 1989.
Likelihood ratio tests for model selection and non-nested hypotheses. Econometrica 57: 307–333.
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