Following the glm() function with a grouped binomial or poisson family, or glm.nb(), P__disp() displays the Pearson Chi2 statistic and related dispersion statistic. Values of the dispersion greater than 1.0 indicate possible overdispersion; values under 1.0 indicate possible underdispersion.
The only argument is the name of the fitted glm or glm.nb function model
P_disp is a post-estimation function, following the use of glm() or glm.nb(). Appropriate with grouped binomial or Poisson glm families.
Pearson Chi2 statistic
Pearson dispersion: Chi2/dof
P__disp must be loaded into memory in order to be effectve. As a function in LOGIT, it is immediately available to a user.
Joseph M. Hilbe, Arizona State University, and Jet Propulsion Laboratory, California Institute of technology
Hilbe, Joseph M. (2015), Practical Guide to Logistic Regression, Chapman & Hall/CRC. Hilbe, Joseph M. (2014), Modeling Count Data, Cambridge University Press
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