[R-sig-ME] bootstrapping random effects using confint() in lme4

[Jonathan Miller]

Dr. Bolker,

I am sorry for what I imagine is a pretty straightforward question.  My
name is Jonathan Miller and I am a Phd student at NCSU in Civil
Engineering.  I have tried to look through online resources for a post on
this, but have not been successful in determining what I need to do.

I have been using lme4 to run a logisitic mixed model and it has worked
very well.   Recently, though, I was interested in determining the
uncertainty in the random effects in my model.  It contains three levels of
random effects, estuaries(32), states(5) and programs(7).  I think the
function confint() is what I need to do, but I am having trouble getting
the outputs for the individual random effects(i.e. estuaries, states,
programs).

My code is below:

m3=glmer(Pres~ Temp_mean + Sal_mean + salsq + NEAR_DIST
         + (1|STATE) + (1 | UNIQUEID) + (1|program),
         data=bighead, na.action = na.exclude, nAGQ=0,
         family=binomial(link="logit"))

confint.merMod(m3,method="boot",nsim=100)

My output just gives me a summary of each fixed effect and each random
effect group.  I think there must be a relatively simple way to get the
output of the bootstrapping for each individual random effect.  It seems
the answer lies in FUN, but I haven't gotten it to work for me yet.


                                            2.5 %      97.5 %
sd_(Intercept)|UNIQUEID  4.720458e-01  0.98029041
sd_(Intercept)|program       3.168555e-01  1.26836628
sd_(Intercept)|STATE        3.019507e-07  1.30279935
(Intercept)                       -6.088106e+00 -3.81230673
Temp_mean                    -6.882682e-02 -0.05817473
Sal_mean                        1.696714e-01  0.20005360
salsq                               -2.253061e+00 -1.89913153
NEAR_DIST                    3.895820e-01  0.50612062


Any help would be greatly appreciated.

Thank you,

Jonathan Miller

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