[R] analyze binary variables in R

Prof Brian D Ripley ripley at stats.ox.ac.uk
Tue Feb 19 08:31:03 CET 2002


On Mon, 18 Feb 2002, christian wrote:

> Hello,
> know somebody a "nice" strategy to analyze a lot of  binary variables with hundred to thousands  of cases.

It depends on the structure of the data, in particular which variables are
responses and which are explanatory, as well as what `a lot' means, since
the number of cases quoted is small.  (There are plenty of examples with
millions or more cases and hundreds of variables.)

The standard approaches are log-linear models for joint responses, and
logistic regression for single ones.  There are more sophisticated ones
involve selecting graphical models, but these need more input from the
subject matter.  The data mining community has a number of visualization
methods, ....

> P.S.
> One nice example for this and something more is the configurational approach from C.Ragin
> http://www.nwu.edu/sociology/tools/qca/qca.html  ,but i fight with the complexity of my data
> and the speed of the contibuted software in TCL/TK and would attempt to implement this in R !

Does any expert statistician recommend that approach?

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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