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Re: ROC, FROC and AFROC

To: Trevor Hastie <hastie@stat.stanford.edu>
Subject: Re: ROC, FROC and AFROC
From: Frank E Harrell Jr <fharrell@virginia.edu>
Date: Thu, 20 Sep 2001 15:10:03 -0400
Cc: s-news@lists.biostat.wustl.edu
Organization: University of Virginia
References: <00e601c141ff$f3040f40$1b6640ab@stanford.edu>
Trevor,

This may help at least indirectly.  Alternatively, if regions in which
abnormalites
are found are discrete and well defined you might consider
a two-sample proportional odds model with clustering within subject
[working independence model with cluster sandwich or cluster
bootstrap intracluster correlation correction.]
That way the lowest value of the ordinal scale would be
especially meaningful.

-Frank Harrell

One possi
 @ARTICLE{alb97gen,
  author = {Albert, Paul S. and Follmann, Dean A. and Barnhart, Huiman
X.},
  year = 1997,
  title = {A generalized estimating equation approach for modeling
random
          length binary vector data},
  journal = Biometrics,
  volume = 53,
  pages = {1116-1124},
  annote = {correlated binary data;GEE;shared parameter models;joint
modeling
           of severity and frequency;compound endpoints}
}

> Trevor Hastie wrote:
> 
> I am looking for some Splus or R  code to do a FROC analysis, in
> particular
> a comparison of the diagnostic ability of two groups. From what I have
> been able to glean from the couple
> of papers that my radioligist consultee has given me to read, FROC
> stands for "Free Response ROC",
> and it arises in radiology where the screener may find none, one, or
> more than one
> abnormality, and rates each of them. This distinguishes it from the
> case where ROC
> analysis is popular, where the unit of measurement is the X-ray or
> image.
> 
> I am open to other approaches as well.
> Thanks
> 
> --------------------------------------------------------------------
>   Trevor Hastie                             hastie@stat.stanford.edu
>   Professor, Department of Statistics, Stanford University
>   Phone: (650) 725-2231 (Statistics)          Fax: (650) 725-8977
>   (650) 498-5233 (Biostatistics)   Fax: (650) 725-6951
>   URL: http://www-stat.stanford.edu/~hastie
>   address: room 104, Department of Statistics, Sequoia Hall
>            390 Serra Mall, Stanford University, CA 94305-4065
> --------------------------------------------------------------------

-- 
Frank E Harrell Jr              Prof. of Biostatistics & Statistics
Div. of Biostatistics & Epidem. Dept. of Health Evaluation Sciences
U. Virginia School of Medicine  http://hesweb1.med.virginia.edu/biostat

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