Timeline for interpreting output for glmmTMB for zero-inflated count data
Current License: CC BY-SA 4.0
7 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| S May 23, 2021 at 1:10 | history | suggested | Marco Plebani | CC BY-SA 4.0 |
I edited the code layout so that it fits the screen better.
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| May 22, 2021 at 17:46 | review | Suggested edits | |||
| S May 23, 2021 at 1:10 | |||||
| May 18, 2020 at 16:15 | vote | accept | alessothegreat | ||
| May 17, 2020 at 8:05 | answer | added | Angelos Amyntas | timeline score: 5 | |
| May 14, 2020 at 17:57 | comment | added | alessothegreat | Okay so I made some progress on understanding the model. You need both the conditional and zero-inflated outputs because... - the conditional output represents the zero portion (or a logistic regression) - the zero inflated output represents a "mixture" model of the two distributions - one for the subgroup who reports zero or close to zero and one for the subgroup who doesn't report zero. However, my collaborator was wondering whether the zero-inflated portion of the model predicts likelihood of a zero value or likelihood of a 1 value? Or is it truly in between 0 to 1. | |
| May 12, 2020 at 16:38 | history | migrated | from stackoverflow.com (revisions) | ||
| May 12, 2020 at 14:05 | history | asked | alessothegreat | CC BY-SA 4.0 |