Timeline for Negative Coefficients for Interaction Term in Dichotomous Variables
Current License: CC BY-SA 4.0
11 events
| when toggle format | what | by | license | comment | |
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| Jul 21, 2023 at 12:17 | vote | accept | Jorge A | ||
| Jul 21, 2023 at 12:13 | comment | added | Jorge A | Done @mkt, thank you for your suggestions. | |
| Jul 21, 2023 at 12:10 | history | edited | Jorge A | CC BY-SA 4.0 |
Added plot of the model via ggeffect.
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| Jul 21, 2023 at 12:03 | answer | added | Peter Flom | timeline score: 1 | |
| Jul 21, 2023 at 11:45 | answer | added | WinzarH | timeline score: -1 | |
| Jul 21, 2023 at 9:42 | comment | added | mkt |
If you use R, the ggeffects package makes this quite easy. As a side note, this kind of plot would be useful to do with the raw data as well (violin plots, mean and confidence intervals, or even mean and all the raw data if you don't have many points). But since your question is about interpreting coefficients, plotting the model output would be most useful to you.
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| Jul 21, 2023 at 9:37 | comment | added | mkt | That's good, but there are better visualisations. Plot drug concentration as a function of gen1, and use two different lines and colours for the 2 levels of smoking. Like this: i.sstatic.net/hg2Wp.png | |
| Jul 21, 2023 at 9:18 | history | edited | Jorge A | CC BY-SA 4.0 |
Added plot of the model.
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| Jul 21, 2023 at 9:17 | comment | added | Jorge A | I'll edit my question then. Thank you @mkt. | |
| Jul 21, 2023 at 8:14 | comment | added | mkt | Always easier to interpret complex models if you plot the model output. | |
| Jul 21, 2023 at 8:07 | history | asked | Jorge A | CC BY-SA 4.0 |
