Timeline for High Standard Errors for Coefficients imply Model is bad?
Current License: CC BY-SA 3.0
7 events
| when toggle format | what | by | license | comment | |
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| Jan 9, 2013 at 13:58 | comment | added | Macro | I agree with you and @gung that more clarification is needed. In fact, I think this question/answer (and others like it) may benefit from some of your own advice. There's no need to treat questions like these as missing data problems :) | |
| Jan 9, 2013 at 13:51 | comment | added | Macro | Peter, It seems to me that whether or not large standard errors indicate a problem depends on the situation. E.g. if the sample size or effect sizes are small, then it's just a fact of life but, if there's large collinearity, you should probably do something about it before "going to town" interpreting the output of your model. I don't disagree with your answer but it presupposes no background info, making it not particularly useful, like fitting a model with no predictors. | |
| Jan 9, 2013 at 0:52 | comment | added | Peter Flom | I agree. This question (as so many) is ambiguous | |
| Jan 9, 2013 at 0:44 | comment | added | gung - Reinstate Monica | Hmm, that's a good point (I should read more carefully). However, I can't tell if the OP means that their SE's are high relative to the coefficients, or just high in general; the question seems ambiguous on this point. | |
| Jan 9, 2013 at 0:20 | comment | added | Peter Flom | No, I was saying "relative to the coefficient" this is true. You can, of course, have a high SE and a high coefficient, that's why my 1) is only one of two possibilities. | |
| Jan 9, 2013 at 0:06 | comment | added | gung - Reinstate Monica | I would not say that a high standard error means that "the coefficient is close to 0". Proximity to 0, & the size of the SE are conceptually unrelated. Perhaps you're thinking of high p-value. | |
| Jan 8, 2013 at 19:23 | history | answered | Peter Flom | CC BY-SA 3.0 |