Timeline for What test to use to determine whether a binary variable is distributed differently among groups
Current License: CC BY-SA 4.0
9 events
| when toggle format | what | by | license | comment | |
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| Oct 17, 2019 at 9:10 | comment | added | baxx | it says binary in the title, and this is the first time that you've commented on that. | |
| Oct 17, 2019 at 5:45 | comment | added | Sheridan Grant | And @baxx I have no idea how to interpret your first comment--of course you're interested in the distribution of the variables. The expected value for each cluster under the null of independence is the average number of positive outcomes across all clusters. If you want to show that a variable is distributed differently across different clusters, you attempt to reject the null hypothesis that the distribution is the same across clusters. You STILL haven't clarified what type of variables you have--your second sentence says "each variable." | |
| Oct 17, 2019 at 5:42 | history | edited | Sheridan Grant | CC BY-SA 4.0 |
all types of outcomes
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| Oct 17, 2019 at 5:39 | comment | added | Sheridan Grant | Oh I misread your question. See edit again. | |
| Oct 8, 2019 at 9:26 | comment | added | baxx | why does it look like that? Are you going to address my previous comment? | |
| Oct 8, 2019 at 5:48 | comment | added | Sheridan Grant | oops, see edit--it looks like your "other variable" is continuous, so ANOVA is the way to go | |
| Oct 8, 2019 at 5:47 | history | edited | Sheridan Grant | CC BY-SA 4.0 |
forgot about continuous variables
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| Oct 8, 2019 at 5:44 | comment | added | baxx | levenes - because i was interested in the distribution of variables. In the case of chi-squared tho, what would the expected value be? Why should I expect a particular variable to have a particular level of response? | |
| Oct 8, 2019 at 5:37 | history | answered | Sheridan Grant | CC BY-SA 4.0 |