Description Usage Arguments Examples
mor: Calculate median odds ratio (MOR) from a random effect variance from a binomial GLMM. inv.mor: Inverse function to get variance from MOR. For a poisson GLMM these functions will transform variances to median *rate* ratios (MRR), and vice versa. mrr and inv.mrr are aliases for mor and inv.mor. See: Interpreting Parameters in the Logistic Regression Model with Random Effects Author(s): Klaus Larsen, J<c2><af>rgen Holm Petersen, Esben Budtz-J<c2><af>rgensen, Lars Endahl Biometrics, Vol. 56, No. 3 (Sep., 2000), pp. 909-914 Equations: mor=exp(sqrt(2*v)*qnorm(0.75)) (MOR function) => log(mor)=sqrt(2*v)*qnorm(0.75) => (log(mor)/qnorm(0.75))^2=2*v => v=((log(mor)/qnorm(0.75))^2)/2 (inverse MOR function)
1 | mrr(v)
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v |
Variance, input to mor and mrr |
1 2 3 4 5 6 7 8 9 10 | # a random effect variance of 1.3 between levels (e.g. sites)...
mor(1.3)
# ...implies that a typical pair of randomly chosen levels
# will differ in odds (or rate, for count GLMMs) by a factor
# of 3.
# inverse function
inv.mor(3)
# mrr and inv.mrr are aliases for mor and inv.mor.
mrr(1.3)
inv.mrr(3)
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