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11-16-2012 07:57 PM

Hi

I am trying to get white standard errors test in my logistic regression. I read a few articles on the internet and came up with the following code:

proc logistic data = LOG;

model log = lsize lprice lsales roa ato chscaled re_ta re_te bmratio indrev TAX86 TAX03/ acov;

run;

However this "/ acov" does not work. Any idea what I'm doing wrong?

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11-16-2012 08:20 PM

I think that would be correct if you were using proc reg. Take a look at: http://pages.stern.nyu.edu/~adesouza/comp/sas.html

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11-16-2012 09:34 PM

These are all for PROC reg how do I what to use for the logistic code?

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11-16-2012 09:44 PM

This seems to work:

data log;

set log;

counter=_n_;

run;

proc surveyreg data=log;

cluster counter;

model log = lsize lprice lsales roa ato chscaled re_ta re_te bmratio indrev;

run;

Just checking that is this appropriate for the logistic model.?

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11-19-2012 07:41 AM

If the variable "log" is a binary variable, then you may want to look at PROC SURVEYLOGISTIC. If it is a continuous variable, then the SURVEYREG code will be a good start. Be aware, though, that it is NOT a logistic model.

Steve Denham

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11-21-2012 07:48 AM

This seems to work, just to confirm my sample size is large, so do I put counter as my cluster variable?.

data log;

set log;

counter= year;

run;

PROC SURVEYLOGISTIC data=log;

cluster counter;

model log = lsize lprice lsales roa ato escaled re_ta re_te bmratio indrev;

run;

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11-21-2012 08:27 AM

Without knowing the data structure and sampling frame, I can't give a full answer. It does seem like a logical choice for the cluster variable, however.

Steve Denham

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04-09-2013 02:23 PM

Hi,

Just to confirm, is it correct then that proc surveyreg with a cluster variable gives White SE's? I can't find anywhere in the documentation for this procedure which actual statistic is used.

Thanks!

Devin Peipert

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04-09-2013 03:18 PM

The default variance estimation is a Taylor series expansion. I don't think this meets the definition of White SE's. The other methods are resampling (jackknife delete one) and Fay's method for balanced replication. So far as I can tell, none of these are robust estimators of the type described by White. However, I would trust the jackknife estimator more than I would a White estimator, as there are weaker assumptions, especially regarding independence.

Steve Denham

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04-09-2013 03:59 PM

Thanks for your quick response, Steve! That is very helpful.

Regards,

Devin Peipert