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Unread 01-07-2015, 18:07
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Re: "standard error" of OPR values

Ether

I wasn't quite sure why you dug up my original post to start this discussion. It seemed out of context with all of your other discussion about adding error estimates. That said, my request was more general, and it seems to be answered more generally by the other computational efforts that have been going on in the 2 related threads.

But one point, I will say that using a fixed effects models with a separate match progression parameter (to capture the most likely source of heteroskedasticity) should lead to parameter estimates that will provide valid error terms using FRC data. But computing fixed effects models are much more complex processes. It is something that can be done in R.

Quote:
Originally Posted by Ether View Post
Sez who? They are the valid least-squares fit to the model. That is all they are. According to what criteria are they then not valid?
That one can calculate a number doesn't mean that the number is meaningful. Without a report of the error around the parameter estimates, the least squares fit is not statistically valid and the meaning cannot be interpreted. This is a fundamental principle in econometrics (and I presume in statistics in general.)
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