Timeline for How to handle bounded [0,1] dependent variable that causes one to fail heteroscedasticity
Current License: CC BY-SA 4.0
11 events
| when toggle format | what | by | license | comment | |
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| May 25, 2018 at 22:30 | history | edited | Mikey |
added 2 more tags
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| May 23, 2018 at 2:05 | vote | accept | Mikey | ||
| May 23, 2018 at 0:57 | answer | added | Ben Bolker | timeline score: 8 | |
| May 22, 2018 at 22:41 | comment | added | Ben Bolker |
you absolutely can use a binomial model, and that would be the right thing to do. In lme4 either cbind(tp,fn) ~ ... or tp/(tp+fn) ~ ..., weights=tp+fn)
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| May 22, 2018 at 21:35 | comment | added | Mikey | @BenBolker The denominators are discrete; the measure is recall (tp / (tp + fn)). However, each observation (a user, in this case) may have a different number in the denominator, which makes me think that a binomial model cannot be used... Does that sound right to you? (I haven't used binomial models in awhile) | |
| May 22, 2018 at 21:31 | comment | added | Mikey | @IsabellaGhement I did not think to use that (nor did I know about it)! However, as Ben pointed out, this package only does zero inflation. The main issue is that this is becoming way too complex for the community I am writing for (in fact, linear mixed-effects models are pushing it already)... So I guess I am wondering how robust linear mixed effects models are to this sort of violation of assumptions? | |
| May 22, 2018 at 20:25 | comment | added | Ben Bolker | It looks like you might have discrete denominators in your data (downward-sloping linear features in your residual plot); can you use a binomial model? | |
| May 22, 2018 at 20:24 | comment | added | Ben Bolker | I don't think glmmTMB can do zero-one inflation (only zero-inflation) ? But you could shrink the data a little bit inward to get (0,1) (e.g. see Smithson and Verkuilen's "better lemon-squeezer" paper) | |
| May 22, 2018 at 19:25 | comment | added | Isabella Ghement | Why not analyze your data using the zero-one inflated beta regression mixed effects modeling using the glmmTMB package, for example? See cran.r-project.org/web/packages/glmmTMB/vignettes/glmmTMB.pdf. | |
| May 22, 2018 at 19:17 | review | First posts | |||
| May 22, 2018 at 19:24 | |||||
| May 22, 2018 at 19:15 | history | asked | Mikey | CC BY-SA 4.0 |