Timeline for How to run chi-squared test on imputed data
Current License: CC BY-SA 4.0
9 events
| when toggle format | what | by | license | comment | |
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| Jul 24, 2023 at 15:45 | history | edited | User1865345 | CC BY-SA 4.0 |
added 11 characters in body
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| S Mar 27, 2023 at 14:40 | history | edited | utobi | CC BY-SA 4.0 |
Adjusted notation to make clearer - the previous way I wrote it was bad
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| S Mar 27, 2023 at 14:40 | history | suggested | Dan Phillips | CC BY-SA 4.0 |
Adjusted notation to make clearer
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| Mar 27, 2023 at 14:37 | review | Suggested edits | |||
| S Mar 27, 2023 at 14:40 | |||||
| S Mar 27, 2023 at 12:35 | history | suggested | Dan Phillips | CC BY-SA 4.0 |
As given by Meg's comment, the statistic in Li, Meng, Ranghunathan and Rubin uses the mean of sqrt(chi-square) not sqrt(mean(chi-square))
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| Mar 27, 2023 at 11:43 | review | Suggested edits | |||
| S Mar 27, 2023 at 12:35 | |||||
| Mar 8, 2014 at 23:06 | comment | added | Meg | I found it useful, but there is an error: In the expression for $r$, the $1/(m-1)$summation term is the variance of the square roots of the test statistics from each imputed data set. As such, the second term should be the mean of the square roots of all test statistics, not the square root of the mean test statistic. | |
| Dec 4, 2013 at 13:02 | comment | added | tomka | @user32145 was this any useful? | |
| Dec 3, 2013 at 22:56 | history | answered | tomka | CC BY-SA 3.0 |