[R-sig-ME] fitting beta and zero mixture model containing both nested and crossed random effects

[Meng Liu]

To whom it may concern,

I am trying to fit a model for a data among which the response value is
within [0,1). I am thinking about fitting the zeros as a complete separate
category from the non-zero data, i.e. a binomial (Bernoulli) model to "==0
vs >0" and a Beta model to the >0 responses. Also, my data contains both
nested factors and crossed factors, which means I need to add nested random
effects and crossed random effects to both logistic model part and beta
model model. However, I didn't find any R packages can do exactly what I
want (By far I found gamlss, glmmTMB, zoib but they either can only assume
random zero or they can only fit repeated measures/clustered data but not
nested and crossed design). Therefore, I am wondering if any one know if
there is any available package or function can do this.

Thank you very much for your help!

Best regards

Meng

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