Because k varies inversely with the degree of overdispersion ,
that overestimation of the degree of overdispersion is very rare for these datasets .
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 .
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 .