Timeline for Linear Regression: Ordinal or dummy independent variables?
Current License: CC BY-SA 3.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Feb 18, 2014 at 14:19 | vote | accept | Damien | ||
| Feb 14, 2014 at 18:02 | comment | added | charles | (1) I don't use JMP so this guess (2) the model shown looks like it is for standard dummy coding and the coefficient estimates shown above for the 'reverse helmert' coding (3) Regarding question: No. if the difference between dummy coefficients (2) and (3) are not significant this had nothing to do with a comparison of (3) and (1). | |
| Feb 14, 2014 at 11:22 | comment | added | Damien | Thanks again for the precisions. My final question is about reading the coefficients. On this picture (i.imgur.com/df9W3Rr.png), I understand that for the two coefficients, the [2-1] compares a variation from 1 to 2, and the [3-2] a variation from 2 to 3, while the estimates given in Prediction expression panel both refer to the first (1) category as a baseline. My question is the following: if the variation from 2 to 3 is not significant in the first panel, does it imply that the coefficient for 3 compared to 1 given in the prediction expression is not significant as well? Thanks! | |
| Feb 13, 2014 at 18:44 | comment | added | charles | I always just look at the partial F test for the variable as a whole, never the individual level p-values. If it is significant -as it is here - the variable is significant (adds information to the model). For traditional dummy coding the individual level p-values tells you if that level deviates significantly from reference level, but nothing about the variable as a whole. (that being said I would be surprised if you included all three possible comparisons and they were all p>0.05, but variable as whole was <0.05, but they are testing different things) | |
| Feb 13, 2014 at 9:16 | comment | added | Damien | Thanks for the explanations! This is very useful. I looked at the "Effect Tests" panel as you suggested and found that the F ratio for the Ordinal variable FightCap is significant. What can I infer from this? Isn't the F ratio contradicting the estimates of the individual modalities? Do I conclude that my variable is not significant, significant, or partially significant? (here is a picture of the result: i.imgur.com/FBQyMZ2.png). | |
| Feb 12, 2014 at 16:53 | history | answered | charles | CC BY-SA 3.0 |
