Analog of least significant difference error bars for proportions

Dear R-list,

	In the R-book, p.464, Michael Crawley recommends that error
bars for bar plots of normally distributed continuous response
variables with categorical explanatory variables be given by
1/2 of the least significant difference, where the least significant
difference is defines as

qt(0.975,degrees_of_freedom)*standard_error_of_the_difference.

The idea is that the above quantity visually conveys whether or not
the means are different more realistically than do standard errors.

	I have analyzed proportions with categorical variables using
the glm function with a binomial error model. I wish to plot a bar
graph with the height of the bars the proportions. Is there a way
to define error bars analogous to the least significant difference bars
described above that can convey the overlap of proportions?
The experimentalists with whom I work just love error bars. I would  
like to
make them as meaningful as possible.

Thanks and best wishes,
Rich
------------------------------------------------------------
Richard A. Friedman, PhD
Associate Research Scientist,
Biomedical Informatics Shared Resource
Herbert Irving Comprehensive Cancer Center (HICCC)
Lecturer,
Department of Biomedical Informatics (DBMI)
Educational Coordinator,
Center for Computational Biology and Bioinformatics (C2B2)/
National Center for Multiscale Analysis of Genomic Networks (MAGNet)
Room 824
Irving Cancer Research Center
Columbia University
1130 St. Nicholas Ave
New York, NY 10032
(212)851-4765 (voice)
friedman at cancercenter.columbia.edu
http://cancercenter.columbia.edu/~friedman/

I am a Bayesian. When I see a multiple-choice question on a test and I  
don't
know the answer I say "eeney-meaney-miney-moe".

Rose Friedman, Age 14