that maximum likelihood estimates of k can be biased upward by small sample size or under - reporting of zero - class events ,
that overestimation of the degree of overdispersion is very rare for these datasets .
Results show that maximum likelihood estimates of k can be biased upward by small sample size or under - reporting of zero - class events , but are not biased downward by any of the factors considered .
Because k varies inversely with the degree of overdispersion , these findings show that overestimation of the degree of overdispersion is very rare for these datasets .