R help - Mar 2010 - penalized maximum likelihood estimation and logistf

Hi, I got two questions and would really appreciate any help from here.
First, is the penalized maximum likelihood estimation(Firth Type Estimation)
only fit for binary response (0,1 or TRUE, FALSE)? Can it be applied to
multinomial logistic regression?
If yes, what's the formula for LL and  U(beta_i)? Can someone point me to
the right reference?
Second, when I used *logistf *on a dataset with binary response, I got the
following error msg:
"Error in if (mx > 1) delta <- delta/mx :
  missing value where TRUE/FALSE needed"

What does this msg mean? does it mean the dataset includes missing response?
I  checked my dataset several times and didn't find anything other than TRUE
or FALSE for the response. Please shed light on this.

Thanks,
Xiaoyan

	[[alternative HTML version deleted]]

Let us look at a piece of the relevant code from "logistf" package:

        iter <- iter + 1
        XW2 <- crossprod(x, diag(pi * (1 - pi))^0.5)
        Fisher <- crossprod(t(XW2))
        covs <- solve(Fisher)
        H <- crossprod(XW2, covs) %*% XW2
        if (firth) 
            U.star <- crossprod(x, y - pi + diag(H) * (0.5 - 
                pi))
        else U.star <- crossprod(x, y - pi)
        delta <- as.vector(covs %*% U.star)
        mx <- max(abs(delta))/maxstep
        if (mx > 1) 
            delta <- delta/mx
 
First, note that this is inside an iterative loop.  The Fisher information
matrix is first formed, and then it is inverted to get `covs'.  This is
where it can get troublesome.  It is very likely in your case that the
`Fisher' information matrix is ill-conditioned, and hence `covs' cannot
be computed.  Consequently, the steplength `delta' for the Newton method
cannot be determined.


Ravi.

____________________________________________________________________

Ravi Varadhan, Ph.D.
Assistant Professor,
Division of Geriatric Medicine and Gerontology
School of Medicine
Johns Hopkins University

Ph. (410) 502-2619
email: rvaradhan at jhmi.edu


----- Original Message -----
From: xiaoyan yu <xiaoyan.yu at gmail.com>
Date: Tuesday, March 9, 2010 11:26 am
Subject: [R] penalized maximum likelihood estimation and logistf
To: r-help at r-project.org

> Hi, I got two questions and would really appreciate any help from here.
>  First, is the penalized maximum likelihood estimation(Firth Type
Estimation)
>  only fit for binary response (0,1 or TRUE, FALSE)? Can it be applied 
> to
>  multinomial logistic regression?
>  If yes, what's the formula for LL and  U(beta_i)? Can someone point 
> me to
>  the right reference?
>  Second, when I used *logistf *on a dataset with binary response, I 
> got the
>  following error msg:
>  "Error in if (mx > 1) delta <- delta/mx :
>    missing value where TRUE/FALSE needed"
>  
>  What does this msg mean? does it mean the dataset includes missing
response?
>  I  checked my dataset several times and didn't find anything other 
> than TRUE
>  or FALSE for the response. Please shed light on this.
>  
>  Thanks,
>  Xiaoyan
>  
>  	[[alternative HTML version deleted]]
>  
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>  
>  PLEASE do read the posting guide 
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