Modified Wald statistics for generalized linear models |
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Authors: | Andreas Oelerich and Thorsten Poddig |
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Institution: | (1) Lehrstuhl für Finanzwirtschaft, Universität Bremen, 28359 Bremen |
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Abstract: | Summary: Wald statistics in generalized linear models are asymptotically 2 distributed.
The asymptotic chi–squared law of the corresponding quadratic form shows disadvantages
with respect to the approximation of the finite–sample distribution. It is shown by means
of a comprehensive simulation study that improvements can be achieved by applying
simple finite–sample size approximations to the distribution of the quadratic form in
generalized linear models. These approximations are based on a 2 distribution with an
estimated degree of freedom that generalizes an approach by Patnaik and Pearson. Simulation studies confirm that nominal level is maintained with higher accuracy compared
to the Wald statistics. |
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Keywords: | Chi– square approximation generalized linear models hypothesis testing quadratic forms logistic regression small sample size |
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