First, see the sub-page "Why Logistic vs. Linear Regression".
NIST gives cursory mention of logistic regression here (under the paragraph titled "Numerical Methods' Forte")
Good overviews on Logistic Regression and implementation, include some (not all) that use the R software package:
[good place to start] By Dr. David Garson at North Carolina State University http://faculty.chass.ncsu.edu/garson/PA765/logistic.htm
from Stanford (Christopher Manning): http://nlp.stanford.edu/manning/courses/ling289/logistic.pdf
from UCLA: http://www.ats.ucla.edu/stat/r/dae/logit.htm
Also see the PowerPoint presentation file "Math456FinalProject-LogisticRegression.ppt" attached at the bottom of this page.
Polytomous Logistic Regression
Multinomial models
Log-linear analysis (see Advanced Log-Linear Models Using SAS (Zelterman))
Crosstab tables and chi-square analysis
Probit and Tobit regression
Poisson regression
Interpreting Odds Ratios in Logistic Regression
Statistica GLZ module
SAS has several packages that will do logistic regression.
proc CATMOD
proc GENMOD
proc LOGISTIC
(Firth)
other?
R has several packages as well:
stat:glm
Design:lrm
Hmisc
rms
logistf
elrm (exact methods for lrm)
Google search "Logistic Regression using R"
(there are others that don't come to mind as this entry is made ... will add later if useful)
General R note: "plogis" has consequently been called the ‘inverse logit’. Check out ?plogis
Many other packages as well (Minitab, S-Plus, etc. etc.)
Applied Linear Regression Models (Kutner)
Categorical Data Analysis Using the SAS System (Stokes)
Introduction to Categorical Data Analysis (Agresti)
Logistic Regression Using the SAS System (Allison)
SAGE Logistic Regression - A Primer (Pampel)
SAGE Interaction Effects in Logistic Regression (Jaccard)
A Guide to Modern Econometrics (Verbeek)
Advanced Log-Linear Models Using SAS (Zelterman)
Data Analysis and Graphics Using R (Maindonald)
Modern Applied Statistics with S-Plus (Venebles)
Logistic Regression course notes (DH)
single-trial syntax, is applicable to binary, ordinal, and nominal response data.
events/trials syntax, is restricted to the case of binary response data.