Timeline for Does it make sense to purposefully run multiple regression with missing values for certain dummy variables?
Current License: CC BY-SA 3.0
6 events
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| Sep 23, 2015 at 17:46 | comment | added | Sympa | Brkn Kybrd can you clarify how you would do that. Using OLS, maximum likelihood, etc..., I am not familiar with a closed form algorithm that could solve for multiple regression coefficients with missing values. | |
| Sep 23, 2015 at 8:51 | comment | added | Brkn Kybrd | Let me specify: Correct, you cannot do it in a matrix framework. However, as multiple regressions do not always use matrices, this means that you can do multiple regressions in the presence of missing values - you just have to use other tools than matrices to arrive at the result. | |
| Sep 22, 2015 at 4:26 | comment | added | Sympa | Splitting the regression into two is not interesting to the question at hand. Meanwhile, your second paragraph contradicts the answer of Scorchi. Given that I specified in the question that I was working with a multiple regression framework, I trust Scorchi's answer is correct. And, yours is probably not wrong but not focused on the relevant methodology. | |
| Sep 21, 2015 at 15:57 | history | edited | Sycorax♦ | CC BY-SA 3.0 |
"Greenspan" is the individual's name; removed boilerplate to conform with CV style
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| Sep 21, 2015 at 15:48 | review | First posts | |||
| Sep 21, 2015 at 15:57 | |||||
| Sep 21, 2015 at 15:43 | history | answered | Brkn Kybrd | CC BY-SA 3.0 |