Hi all,

I’ve been searching at length for a way to figure out how to calculate the
ICC for a mixed effects quasipoisson model in R from the output below (i.e.,
intercept only model) and can't figure out the correct equation to use. For
example, I've run mixed effects logistic regression models for which I used
the following equation:

               c<-a*a

               icc<-c/(3.289868+c)

[a being the standard deviation of the intercept]



I'm not sure what the corollary type of equation is for quasipoisson mixed
models.



If you had any suggestions I would greatly appreciate it.



Best,

Elizabeth





womentxengintonly <- glmmPQL(NewSpecOut_SUM ~ 1, random = ~1 |NEPEC3N,
family =quasipoisson, data = women)





summary(womentxengintonly)



Linear mixed-effects model fit by maximum likelihood

Data: women

  AIC BIC logLik

   NA  NA     NA



Random effects:

Formula: ~1 | NEPEC3N

        (Intercept) Residual

StdDev:   0.4679934  7.26936



Variance function:

Structure: fixed weights

Formula: ~invwt

Fixed effects: NewSpecOut_SUM ~ 1

               Value  Std.Error   DF  t-value p-value

(Intercept) 3.046308 0.04805773 4960 63.38852       0



Standardized Within-Group Residuals:

       Min         Q1        Med         Q3        Max

-1.0333625 -0.5507037 -0.3717204  0.2138915 12.4856954



Number of Observations: 5099

Number of Groups: 139

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