[R] How to collect better estimations of a logistic model parameters, by using bootstrapping things ?

From: Laurent Valdes <valderama_at_gmail.com>
Date: Thu 25 Aug 2005 - 06:52:42 EST

Dear all,

I know that when using R, people should have a sufficient level in statistics.
As well, I'm not a genius, when dealing with logistic regressions. I would like to construct ICs, IPs, for a logistic regression, but the point is I have just 41 observations. I had a look at the Design package and noticeably the lrm function, but I'm still not able to reduce the IC's, as I was trying to do this in SPSS (but do not like it).
I have heard of a mean to do this by using bootstrap, but I'm still waiting to find the right way to use it.

As well I would like to find a fine way to do stepwise forward selection In R, as I am not sure wich kind of variable may be involved in the model, which is composed with 13 numeric variables, and a dichotomic variable named "expatriation". I have got a total of 41 observations, as mentionned above.

I'm using R on macintosh, I have used the function lrm, brlr, bootstrap (but for others uses than logistic regressions), and I am looking for a great and paved way to do Confiance Intervals, and to compute significance values for each of the logistic model's parameters, by using R ans bootstrapping, of course.

Any ideas ?

Laurent.

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