fitting beta and zero mixture model containing both nested and crossed random effects

---------- Forwarded message ----------
From: Guillaume Chaumet <guillaumechaumet at gmail.com>
Date: 2018-06-10 17:03 GMT+02:00
Subject: Re: [R-sig-ME] fitting beta and zero mixture model containing
both nested and crossed random effects
To: Meng Liu <liumeng at usc.edu>


brms: https://cran.r-project.org/web/packages/brms/index.html

2018-06-09 21:06 GMT+02:00 Meng Liu <liumeng at usc.edu>:

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

        [[alternative HTML version deleted]]