Timeline for Fitting lower-order interactions with higher order main effects
Current License: CC BY-SA 3.0
5 events
| when toggle format | what | by | license | comment | |
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| Nov 18, 2013 at 14:55 | vote | accept | rjweyant | ||
| Nov 14, 2013 at 19:06 | comment | added | AdamO | Well, if statistical significance alone resolves your concerns, I am now concerned for other reasons! As long as the interaction term(s) is/are nested in the product of main effects, then the interpretation of the test is conserved, albeit more difficult. With quadratic effects, the interpretation of the 1st order effect is the instantaneous rate of change at the apex of the parabola. I'd have to sit down with a 3d plotter to really see what the differences are btn these various modeling approaches. | |
| Nov 14, 2013 at 14:53 | comment | added | rjweyant | I did an LRT on the 4 terms and this was significant, so my concern is resolved, but I'm still curious about the general problem. It seems that we include all lower order terms/main effects when fitting interactions and polynomials to avoid forcing the function through the origin, or another unnatural 0. When we fit a quadratic function and only a linear interaction, it forces an unnatural point where all the curves will cross. So while there might not be theoretical problems with this interaction, is it reasonable to discount it due to what it means within the problem? | |
| Nov 13, 2013 at 22:39 | history | edited | AdamO | CC BY-SA 3.0 |
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| Nov 13, 2013 at 21:18 | history | answered | AdamO | CC BY-SA 3.0 |