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In GLMs, quasi-likelihood estimation is a way to allow over- or under-dispersion by choosing an appropriate variance function.

In GLMs, quasi-likelihood estimation is a way to allow over- or under-dispersion by choosing an appropriate variance function. It's often used for binary or count data, e.g. in quasi-binomial or quasi-Poisson models; there it does not correspond to any actual count distribution.

Wikipedia has an article https://en.wikipedia.org/wiki/Quasi-likelihood with further information and references.