[R-sig-ME] Mixed effects model with many zeros

Austen Anderson @@nder@8 @end|ng |rom y@hoo@com
Thu Jun 4 23:48:41 CEST 2020

Hi, I've got a set of longitudinal data with negative affect as the dependent variable. Negative affect was measured by 10 items asking about how much of the day the participant felt 10 different negative emotions (ordinal scale from 0-4). The modal response to that survey was 0 for all ten items, resulting in a large number of zero's for that variable along with a strong right skew. I've been exploring CrossValidated and other sources to get a sense of what my options are for modeling this data. I've read about Tweedie models, Tobit (censored) models, hurdle models, beta distribution models, and zero-inflated gamma models. As far as I could understand, the Tweedie model seemed reasonable and I modeled it this way:
neg_nat_mod_tweed <- glmmTMB(negaff ~ enjoynat_c + enjoynat_mean + daynum + (1|MRID),                          data = daily,                         family = tweedie)summary(neg_nat_mod_tweed)

Family: tweedie  ( log )
Formula:          negaff ~ enjoynat_c + enjoynat_mean + daynum + (1 | MRID)Data: daily
     AIC      BIC   logLik deviance df.resid   4637.0   4683.6  -2311.5   4623.0     5753 
Random effects:
Conditional model: Groups Name        Variance Std.Dev. MRID   (Intercept) 1.19     1.091   Number of obs: 5760, groups:  MRID, 782
Overdispersion parameter for tweedie family (): 0.248 
Conditional model:               Estimate Std. Error z value Pr(>|z|)    (Intercept)   -1.653574   0.075059 -22.030  < 2e-16 ***enjoynat_c    -0.132666   0.033037  -4.016 5.93e-05 ***enjoynat_mean  0.009201   0.134737   0.068    0.946    daynum        -0.087213   0.005578 -15.636  < 2e-16 ***---Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

I have a few questions. First, does it seem like this is a reasonable way to analyze this data? If not, do you have other recommendations? Second, while the manual for GLMMtmb provides the Tweedie model as an option, here (https://cran.r-project.org/web/packages/glmmTMB/vignettes/glmmTMB.pdf) it says it is not yet implemented. Does anyone know if this model is trustworthy? Lastly, it mentions that the link function is log. I am still learning about how link functions work and I am not sure how to make sense of the coefficients because in their current form the negative intercept makes no sense. Can you offer some guidance on interpretation?
Thank you for your time,Austen
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