Timeline for Standardizing variables with negative values in R
Current License: CC BY-SA 4.0
11 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Feb 18, 2019 at 23:14 | history | edited | kjetil b halvorsen♦ |
edited tags
|
|
| Feb 10, 2019 at 1:21 | vote | accept | user10831611 | ||
| Feb 10, 2019 at 1:21 | vote | accept | user10831611 | ||
| Feb 10, 2019 at 1:21 | |||||
| Feb 8, 2019 at 22:03 | answer | added | Ben | timeline score: 1 | |
| Feb 1, 2019 at 14:58 | answer | added | Brent Hutto | timeline score: 2 | |
| Feb 1, 2019 at 14:30 | comment | added | user10831611 | @BrentHutto I'm not sure if I understand the difference between the two. Is rescaling the same as the scale function in R? If so, then my understanding is that log transformation is necessary beforehand (i.e. #6 on stats.stackexchange.com/questions/156791/…) | |
| Feb 1, 2019 at 14:04 | comment | added | Brent Hutto | I'm not clear on the motivation for a log transformation. I also wonder if you mean "standardize them" or simply "rescale them". Rescaling and standardizing are two different operations. But unless I'm failing to miss the point, I think the answer is yes. You can definitely standardize variables without ever log transforming them. | |
| Feb 1, 2019 at 13:59 | history | migrated | from stackoverflow.com (revisions) | ||
| Feb 1, 2019 at 13:12 | comment | added | user10831611 | @AdamWheeler thank you!! I just have a quick question—If I were to transform one dependent variable with negative values in this way, would I do the exact same transformation to the other dependent variables and independent variable? | |
| Feb 1, 2019 at 12:26 | comment | added | James Phillips | I suggest visually inspecting scatterplots of each independent variable versus the dependent variable to see if there is any obvious transformation such as exp or log that would help in the regression. This is usually fast and easy to do. | |
| Feb 1, 2019 at 12:08 | history | asked | user10831611 | CC BY-SA 4.0 |