Overdispersion tests in #rstats

May 3, 2017
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(This article was first published on R – christopher lortie, and kindly contributed to R-bloggers)

A brief note on overdispersion

Assumptions

Poisson distribution assume variance is equal to the mean.

Quasi-poisson model assumes variance is a linear function of mean.

Negative binomial model assumes variance is a quadratic function of the mean.

rstats implementation

#to test you need to fit a poisson GLM then apply function to this model

library(AER)

dispersiontest(object, trafo = NULL, alternative = c(“greater”, “two.sided”, “less”))

trafo = 1 is linear testing for quasipoisson or you can fit linear equation to trafo as well

#interpretation

c = 0 equidispersion

c > 0 is overdispersed

Resources

  1. Function description from vignette for AER package.
  2. Excellent StatsExchange description of interpretation.

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