Timeline for How to interpret insignificant intercept in logistic regression with orthogonal polynomial encoding
Current License: CC BY-SA 4.0
5 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Aug 2, 2020 at 3:55 | comment | added | kjetil b halvorsen♦ | That is good, but what you jave wrote in the Q is different from what in the comment .... ? can you correct, and explain? Maybe share (a link to) the data, so we can show some examples in answers, that way it should be clearer. | |
| Aug 1, 2020 at 23:29 | comment | added | Harry | I have added the section on Model$predict. I think I have added everything included in this model in the code now. | |
| Aug 1, 2020 at 23:18 | comment | added | kjetil b halvorsen♦ | Can you please add that information to the Q as an edit, togetger with relevant code, so we can be sure what you are doing? | |
| Aug 1, 2020 at 21:40 | comment | added | Harry | The numerical values used are 1, 2, 3. Model$predict[1:3] yields 0.5416667 0.5416667 0.7261905. Is this what you need? Sorry if it's not, I'm a little out of my depth. | |
| Aug 1, 2020 at 21:19 | history | answered | kjetil b halvorsen♦ | CC BY-SA 4.0 |