Timeline for What are the disadvantages of using mean for missing values?
Current License: CC BY-SA 4.0
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| Oct 27, 2021 at 1:06 | comment | added | user215517 | @benso8 You say: "Using the mean for missing values is not ALWAYS a bad thing." so can you give a realistic example where this approach would be a neutral or a good thing? | |
| Oct 26, 2021 at 22:55 | history | edited | benso8 | CC BY-SA 4.0 |
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| Apr 4, 2020 at 18:41 | comment | added | benso8 | @gung-ReinstateMonica I was providing additional information to the original question. The original question stated "Why is this variance reduction considered as a bad thing? " I wanted to clarify that it is not always a bad thing. I then confirmed that it can, however, decrease the variance and gave an example of where that can be an issue. | |
| Apr 4, 2020 at 16:00 | comment | added | gung - Reinstate Monica | I don't understand how your example supports the claim that it's not always bad. Your example is that the resulting $R^2$ is biased to be too high. Why would that be advantageous? Am I missing something here? | |
| Apr 3, 2020 at 6:38 | history | edited | Nick Cox | CC BY-SA 4.0 |
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| Apr 3, 2020 at 4:25 | history | edited | benso8 | CC BY-SA 4.0 |
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| Apr 3, 2020 at 3:59 | history | edited | benso8 | CC BY-SA 4.0 |
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| Apr 3, 2020 at 2:39 | history | edited | benso8 | CC BY-SA 4.0 |
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| Apr 2, 2020 at 22:14 | history | edited | benso8 | CC BY-SA 4.0 |
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| Apr 2, 2020 at 21:56 | history | edited | benso8 | CC BY-SA 4.0 |
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| Apr 2, 2020 at 21:47 | history | answered | benso8 | CC BY-SA 4.0 |