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I'm building my GLMM using r.
model <- glmer(views ~ comments_disabled + theme + weeks + tags + (1 | channel), data=video, family="poisson"(link="log"))
Channel – YouTube account the video was uploaded from ( all account names, e.g.Netflix, star wars etc)
Views – Number of times the video was viewed ( that observed over unequal time interval)
Comments_disabled – Whether the channel disabled other users from commenting on the video (no = comments enabled, yes = comments disabled)
Theme – Category of the video (e.g. ‘Drama’, ‘Family’ etc)
Weeks – Number of weeks available on YouTube to date
Tags – Number of tags, key words assigned to the video that users can search for within YouTube
It gives some warning messages:
1: In checkConv(attr(opt, "derivs"), opt\$par, ctrl = control\$checkConv, : Model failed to converge with max|grad| = 0.00141064 (tol = 0.001, component 1)
2: In checkConv(attr(opt, "derivs"), opt\$par, ctrl = control\$checkConv, : Model is nearly unidentifiable: very large eigenvalue - Rescale variables?
I'm don't really understand the meanings of these warnings and how can I fix them.
Also, is it correct that channel is the only random effect in my model?