Hallo there,

 greetings from Germany.

 I have a simple question for you.

 I have run a binary logistic model, but there are lots of outliers distorting the real results.

 I have tried to get rid of the outliers using the following commands:

 remove = -c(56, 303, 365, 391, 512, 746, 859, 940, 1037, 1042, 1138, 1355)
 MIGRATION.rebuild <- glm(MIGRATION, subset=remove)
 influence(MIGRATION.rebuild) 
 influence.measures(MIGRATION.rebuild)

 BUT it did not work.


 My question is:

 *Do you know a simple R-command which erases outliers and rebuilds the model without them?*

 I am including my model below so that you may have an idea of how I am trying to do it.

 Thanks in advance for your help.

 Francisco M. da Rocha

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