Timeline for Is it valid to use logistic regression for a dead or alive outcome variable?
Current License: CC BY-SA 4.0
14 events
when toggle format | what | by | license | comment | |
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Aug 18, 2020 at 11:02 | answer | added | BigBendRegion | timeline score: 2 | |
Aug 12, 2020 at 0:56 | comment | added | user293790 | Compare the percentage alive between 2 groups over time. | |
Aug 12, 2020 at 0:55 | comment | added | user293790 | The response variable is whether a subject is still alive at any time. Don’t suggest coxph because I didn’t measure time until death. | |
Aug 12, 2020 at 0:54 | comment | added | Dave | Then your outcome variable is how many deaths there are, not whether or not a subject lives or dies. What are you trying to model? | |
Aug 12, 2020 at 0:53 | comment | added | user293790 | If I coded the death per ID number as a count, wouldn’t that be a count? Of course anything can only die once. | |
Aug 12, 2020 at 0:51 | review | Low quality posts | |||
Aug 12, 2020 at 4:55 | |||||
Aug 12, 2020 at 0:50 | comment | added | Dave | You don’t have zero-inflated data. You have imbalanced classes. Poisson regression does not come into play. Poisson would be when the response is a count. Your response is a category that you happen to code as 0 and 1, but those numbers have no meaning. (You could flip which class corresponds time which number without changing much of anything.) | |
Aug 12, 2020 at 0:43 | history | edited | user293790 |
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Aug 12, 2020 at 0:42 | comment | added | user293790 | If someone suggests poisson regression, I’ll say no because I’ll have to use quasi poisson with my zero inflated data, or use NBGLMM which I don’t want to do. | |
Aug 12, 2020 at 0:42 | review | First posts | |||
Aug 12, 2020 at 2:32 | |||||
Aug 12, 2020 at 0:40 | comment | added | user293790 | Rarely every does death happens | |
Aug 12, 2020 at 0:39 | comment | added | user293790 | There’s a lot of alives and few dead. | |
Aug 12, 2020 at 0:38 | comment | added | Dave | What is zero-inflated in this case, the response variable? | |
Aug 12, 2020 at 0:34 | history | asked | user293790 | CC BY-SA 4.0 |