Advances and Applications in Statistics
Volume 10, Issue 1, Pages 55 - 73
(October 2008)
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STATISTICAL INFERENCE FOR A BIVARIATE POISSON REGRESSION MODEL
Kent Riggs (U. S. A.), Dean M. Young (U. S. A.) and James D. Stamey (U. S. A.)
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Abstract: Bivariate Poisson regression models allow for joint estimation
of two Poisson counts as a function of possibly different covariates. We use
vector calculus to derive the Wald, score, and likelihood ratio statistics for
testing a single coefficient parameter vector. We compare the power of these
three statistics using a limited Monte Carlo simulation study. We also develop
a Wald
statistic for testing the
equality of two regression coefficient vectors. Lastly, we apply the
newly-derived test statistics to an Australian health survey data set. |
Keywords and phrases: bivariate Poisson regression, asymptotic tests, simulation. |
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