[R-sig-ME] Mixed models with a dichotomous outcome, random slopes, and accounting for autocorrelation

[Adam Roebuck]

Hello,

I am attempting to set up a multilevel model with two grouping variables
(team and year), random slopes for day of the year, and accounting for
autocorrelation. I have a number of different outcome variables I can use.
When the outcome variable is continuous, I can set up a simple growth model
using the nlme package that looks something like the following:

model1 <- lme(continuous_outcome ~ 1 + Predictor_X + Day,

random = ~1 + Day | Team | Year, data = dat, method = "REML",

control=list(opt="optim"), correlation = corAR1()

However, I now want to build a model with a dichotomous outcome variable.
As far as I know, nlme cannot account for all of the above and a
dichotomous outcome. I have, however, seen a few references to glmer (in
the lme4 package) and glmmTMB being capable of such. I've gone back through
the archives, though, and am not seeing any clear explanations on how to
set up such a model.

Using the parameters above and the variables I specified, could someone
please help specify what that model might look like in R or at least point
me in the right direction?

Thanks,
Adam

-- 
*Adam Roebuck*
University of Connecticut | School of Business
Doctoral Candidate | Management
2100 Hillside Rd., Unit 1041
Storrs, CT 06269
(248) 613-9609

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