Timeline for NA in glm model
Current License: CC BY-SA 3.0
12 events
| when toggle format | what | by | license | comment | |
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| May 17, 2016 at 3:03 | history | tweeted | twitter.com/StackStats/status/732406098750279680 | ||
| May 16, 2016 at 19:38 | history | migrated | from stackoverflow.com (revisions) | ||
| May 16, 2016 at 6:04 | vote | accept | learner | ||
| May 16, 2016 at 6:04 | answer | added | learner | timeline score: 1 | |
| May 16, 2016 at 6:03 | comment | added | eipi10 |
When you have a variable that's a linear combination of other variables (for example, if you have independent variables x, w, and z, but x = aw + bz (where a and b are any real constants other than zero), then x is a linear combination of w and z) you're essentially asking glm to estimate n + 1 regression coefficients with only n equations. But there's no unique solution in that case.
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| May 16, 2016 at 6:02 | comment | added | eipi10 |
glm drops one of the linearly dependent variables from the regression and returns NA for that coefficient. It has nothing to do with whether there are NA values in your data.
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| May 16, 2016 at 5:45 | comment | added | learner | @eipi10 How does it relate to producing NA then ? | |
| May 16, 2016 at 5:44 | comment | added | learner | @shreyasgm I already metioned about this . Please provide explanation in context with logistic regression and cite some good resources if you can. | |
| May 16, 2016 at 5:44 | comment | added | eipi10 | It looks like TotalVisits is the sum of InpatientDays, ERVisits, and OfficeVisits. | |
| May 16, 2016 at 5:41 | comment | added | shrgm | Possible duplicate of stackoverflow.com/questions/7337761/… . Your variables are not all linearly independent. | |
| May 16, 2016 at 5:41 | comment | added | Adam Quek | Can't figure out your issue. But are you sure having MemberID as a predictor is wise? | |
| May 16, 2016 at 5:30 | history | asked | learner | CC BY-SA 3.0 |