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

[Laurent Valdes]

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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