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Underdispersion is when there is less variability than there 'ought' to be in the data. Eg, the variance of counts could be less than the mean, whereas the variance of a Poisson should equal the mean.

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How to correct underdispersion in logistic regression

Getting a residual mean deviance around 0.63 is perfectly normal for binary regression and it does not indicate underdispersion or overdispersion. … There is actually no such thing as underdispersion or overdispersion for binary regression. …
Gordon Smyth's user avatar
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4 votes
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Count process with standard deviation proportional to its mean

Mean-variance relationships are defined for families of probability distributions, especially families indexed by a single parameter. As we vary the unknown parameter, both the mean and the variance o …
Gordon Smyth's user avatar
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