Timeline for Why do I get an error when trying to impute missing data using PMM in MICE package in R? [closed]
Current License: CC BY-SA 3.0
11 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Oct 17, 2018 at 13:10 | history | closed |
mkt kjetil b halvorsen♦ Michael R. Chernick Carl Peter Flom |
Not suitable for this site | |
| Oct 16, 2018 at 9:15 | review | Close votes | |||
| Oct 17, 2018 at 13:10 | |||||
| Oct 16, 2018 at 8:08 | comment | added | Nikhil Kumar | mice(mydata[,c(-1)],m=3,seed=123,maxit=500, method='cart') | |
| Mar 29, 2018 at 2:49 | history | tweeted | twitter.com/StackStats/status/979188746099871744 | ||
| Mar 27, 2018 at 20:32 | comment | added | rolando2 | See both answers at stats.stackexchange.com/questions/76488/… | |
| Mar 27, 2018 at 14:25 | comment | added | user2279481 | kaggle.com/c/house-prices-advanced-regression-techniques/… Will give you the answer for the problem | |
| May 24, 2016 at 20:19 | comment | added | Henry | You might want to read jstatsoft.org/article/view/v045i03/v45i03.pdf especially pages 22 26 and 42 which mention collinearity | |
| May 24, 2016 at 20:07 | comment | added | Emma | Thanks @Henry, it is very likely the problem lies with the collinearity but variables that are highly correlated are of interest to me. Would this mean the other imputation methods I tried would result in low quality data or is it mainly a problem with predictive mean matching? | |
| May 24, 2016 at 6:56 | comment | added | Henry | Presumably you are trying to invert an non-invertible matrix. Possibly one of your variables is a linear combination of others of your variables | |
| May 24, 2016 at 5:03 | review | First posts | |||
| May 24, 2016 at 6:26 | |||||
| May 24, 2016 at 4:58 | history | asked | Emma | CC BY-SA 3.0 |