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Jul 6, 2023 at 13:08 comment added EdM I must have confused the Anova() display of the model with Mating_time as the predictor (1 d.f.) with that of the first model with Round as a predictor. There were already 8 d.f. associated with Round in that first model, meaning that it must already have been encoded as a factor variable. I'll edit my answer accordingly, while keeping a warning about the difference between encoding such variables as numeric versus categorical.
Jul 5, 2023 at 20:42 history edited Blanca CC BY-SA 4.0
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Jul 5, 2023 at 20:12 vote accept Blanca
Jul 5, 2023 at 13:41 answer added EdM timeline score: 1
Jul 4, 2023 at 20:26 comment added Blanca First, Lukas you're right. I don't know how I didn't spot this. I guess I was tired. EdM, fixed this and the output now looks more like I expected. Added a last question in the edited version. Feel free to comment.
Jul 4, 2023 at 20:24 history edited Blanca CC BY-SA 4.0
Added new script from the changes proposed by Lukas Lohse and EdM
Jul 4, 2023 at 18:10 comment added EdM In addition to the comment by @LukasLohse, you have to remove all data lines for an individual after the time of the individual's event. In a situation with at most one event per individual, someone who had the event is no longer at risk at later times and thus must be removed from analysis. Coding those later times after an event as representing either events or non-events is not appropriate. After an event, the individual is no longer properly considered part of the study.
Jul 4, 2023 at 15:24 comment added Lukas Lohse mating_time is the response. You need to swap it and round in your model. round isn't even binary.
Jul 4, 2023 at 14:40 history edited Blanca
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Jul 3, 2023 at 20:35 history asked Blanca CC BY-SA 4.0