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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