Timeline for How to account for missing observations in multivariate regression?
Current License: CC BY-SA 4.0
6 events
when toggle format | what | by | license | comment | |
---|---|---|---|---|---|
Jul 18, 2018 at 19:47 | vote | accept | Tom Witten | ||
Jul 18, 2018 at 17:22 | comment | added | MkL | Right, if I got your "rule" correctly, your model should learn kind of that way. And addtionally some "rule" for the case where the indicator column is 0 saying feedback percentage is not avaialble. | |
Jul 18, 2018 at 17:07 | comment | added | Tom Witten | Ah cheers man, really appreciate that! so when i come to interpret the results i would say something like "a seller that has a feedback percentage can expect an x% increase/derease in revenue and, for those that do, each additional percentage point loss decreases revenue by x amount" ? would that be correct? | |
Jul 18, 2018 at 17:07 | comment | added | Kevin Li | I disagree with the idea that this is considered "standard". It's like saying that the lack of a value has some kind of effect. It would be useful to include it if the OP was interested in studying the effect that a missing value has on his response variable, but in general is not standard. | |
Jul 18, 2018 at 17:05 | review | First posts | |||
Jul 18, 2018 at 17:57 | |||||
Jul 18, 2018 at 17:01 | history | answered | MkL | CC BY-SA 4.0 |