Dear Brad
Dear Jinko
Dear David
Sorry for the noise out of nothing.
It was because of my ignorance and misunderstanding of algorithms of
elrm.
elrm is great for the assessment of multivariable model where Stata
simply runs out of memory fails, while Stata can make exact calculations
on one variable.
What scared on the first place was variation in p-values when changing
'iter' option.
Now I work with small dataset of 73 trials with 59 successes and trying
to handle with categorical independent variables. Could you please
suggest which number of iterations and burnIn is better to choose?
Could you please comment how to interpret p-value for joint effect? For
instance, I couldn't get the example in
Zamar D, McNeney B and Graham J. elrm: Software Implementing
Exact-like Inference for Logistic Regression Models. Journal of
Statistical Software 2007, 21(3).
on page 9, where p value of 0.76555 is consistent with the model used.
And finally, could you please tell if I have to cite numbers number of
iterations and burnIn in publication?
With best regards
Denis
P.S. Sorry for naive questions
? ???, 04/02/2011 ? 14:52 -0800, Brad McNeney ????:
You might get a more useful response if you CC the package maintainer, David Zamar, who I don't think is a member of this list. I wonder if you could elaborate on the reason (and provide a test data set) for your distrust of the output. Brad ----- Original Message ----- From: "Den" <d.kazakiewicz at gmail.com> To: "R-help" <r-help at r-project.org> Sent: Friday, 4 February, 2011 8:44:04 AM Subject: [R] exact logistic regression Hate to say that, but it looks like Stata is way above R, considering exact logistic regression. To use elrm() I have to aggregate my data,which is really time consuming when I look for the way out through many variables. But the worst thing is that I am not not sure if I can trust to p-values in output. I would be happy,however, if someone could contradict me on this issue. With best regards Denis
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