Timeline for fixed effects model with upper level predictors and cross-sectional data
Current License: CC BY-SA 3.0
3 events
| when toggle format | what | by | license | comment | |
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| Jun 1, 2017 at 8:46 | comment | added | Jonathan Marin | Imagine a regression model with 7 observations. That would not be convincing. It is kind of the same you do when clustering on 7 countries. The standard errors from this will not produce anything you can rely on. you could still cluster, but instead try cluster over regions within countries (if you have data on that). You assume there is no correlation between regions (which might be wrong), but I guess you will still capture some of the clustering in your data. | |
| Jun 1, 2017 at 8:24 | comment | added | Erdne Htábrob | sorry for the confusion with the fixed effects name. This is a bit different than the panel data application, I should have referred to country dummies but in political science the name "fixed effects " often flies around for this type of model. I understand the limits of clustered standard errors, but surely not clustering them and assuming that respondents are independent observations is equally wrong/worse? | |
| Jun 1, 2017 at 8:16 | history | answered | Jonathan Marin | CC BY-SA 3.0 |