Graphical Methods for Binary Data
Sanford Weisberg
Department of Applied Statistics, School of Statistics, University of Minnesota
In simple regression, the usual graph of the response versus
the predictor
contains virtually all the information available about the regression
problem, and it therefore provides a good summary of the problem.
In regression with a binary response, this graph is not particularly
useful becuase the response is only a zero or a one. After a brief
review of
binary regression basics, the relationship between graphs and logistic
regression models will be derived and discussed. More general ideas for
exploring binary regression through graphics are then presented.
The final part of the talk covers model checking. In linear models,
model checking graphs are based on the fundamental result that given a
correct model, residuals and the predictors are uncorrelated, but they are
generally not independent for an incorrectly specified model. In binary
regression, this property does not hold. so exactly how residuals are to
be used in model checking is unclear. Alternative plots called marginal
model plots that do not use residuals will be described and discussed.
Refreshments: 3:30 - 4:00 p.m. Tuesday,
May 5, at 327 Yost
Talk: 4:00 - 5:00 p.m. Tuesday, May 5, at 327 Yost.
Questions? jiayang@sun.cwru.edu
Wed Aug 13 13:54:29 EDT 1997