So what problems do I need to look out for, and what diagnostics should I use. Since the data will automatically be heteroscedastic I am not sure there is any point in testing for that.

- Thread starter noetsi
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So what problems do I need to look out for, and what diagnostics should I use. Since the data will automatically be heteroscedastic I am not sure there is any point in testing for that.

"If the probability is between .20 and .80, then the log odds are almost a linear function of the probability."

How do you know if this occurs. That is how can you test if the probabilities like between .2 and .8

The residuals will be heteroskedastic and non-normal. You can use white SE for the former. But given the later is true can you use t test at all for the slopes?

How do you know if this occurs. That is how can you test if the probabilities like between .2 and .8

The residuals will be heteroskedastic and non-normal. You can use white SE for the former. But given the later is true can you use t test at all for the slopes?

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Otherwise, I think you treat everything else as you typically do in OLS.

Otherwise, I think you treat everything else as you typically do in OLS.

Well the y_hat values are just the predictions. Maybe you could look at the predictions and see if any are in that range...

I will have hundreds, probably thousands of cases so the sample size will not be small.