[R-sig-ME] R-sig-mixed-models Digest, Vol 69, Issue 18

[Kumiko Fukumura]

Hi,

RE: "Hauck-Donner effect"

I was wondering if you could possibly clarify whether Hauck-Donner effect affects coefficients for interactions only or it also affects fixed effects as well. In my experience, it seems to vary: in some situations, many zeros in one or more condition appeared to influence the estimate for the interaction only, but they also seem to influence fixed effects in other situations (though the fixed effects estimates were sensible when the interaction was removed from the model).  Another question is what we can do under such situations - having many zeros also seem to influence the results of model comparisons (using "anova" functions) as well as coefficient estimates - I noticed that some recommended the use of model comparisons to address the problem, but it doesn't seem to help much. Removing some conditions is a possibility, but it's a bit shame because we cannot take into account the whole data set in our analyses.  I'd be very grateful if you could give us any more information that you know about this phenomenon. Thank you very much in advance.

Best wishes
Kumiko


Kumiko Fukumura
University of Strathclyde


>You should look up/Google for "Hauck-Donner effect" (you can find a discussion in Venables and Ripley's book), which refers to the situation >where the approximation used to compute confidence intervals on GLM(M)s breaks down for strong effects.
>You should use explicit model comparison (?update, ?anova, ?drop1) to test the difference between models with and without the intercept term.

>However, you might want to be careful with the all-zero case, as it will lead to an infinite estimate (in theory) of the interaction coefficient -- in >practice it will just lead to a very large, poorly constrained estimate.
>You could try a Bayesian method, or you could just try leaving out that category and make sure that the qualitative results of your analysis remain >unchanged ...

  Ben Bolker



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End of R-sig-mixed-models Digest, Vol 69, Issue 18