CODEWITHSUNDEEP
rregression
baz
baz

Reputation: 7117

is there a way to only include factors that are significant at P<0.05 in a backward elimination in logistic regression

When doing a backward elimination using the step(), is it possible to only include those factors that are significant, for example, at P<0.05?

I am using this line at the moment 

step(FulMod3,direction="backward",trace=FALSE)

to get my final model.

Upvotes: 0

Views: 2045

Answers (1)

Ben Bolker
Ben Bolker

Reputation: 226731

Answers to these questions give starting points

In particular they point you towards fastbw in the rms package, which can be used in conjunction with rms::lrm (logistic regression). They also explain why stepwise regression via p values is often a really, really, really, BAD idea: see also http://www.stata.com/support/faqs/stat/stepwise.html . There are a few contexts where it is appropriate (otherwise Frank Harrell, the author of the rms package and crusader against foolish uses of stepwise regression, wouldn't have written fastbw), but they are relatively rare, usually dominated by (e.g.) penalized regression approaches or by stepwise approaches via AIC (as implemented in step): see e.g. https://stats.stackexchange.com/questions/13686/what-are-modern-easily-used-alternatives-to-stepwise-regression and https://stats.stackexchange.com/questions/20836/algorithms-for-automatic-model-selection

Upvotes: 6

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