Thanks for teaching me something new. :)
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The probem is that in the case of model 2 the standard error terms
reduce to a vector of length one. Since subsetting with '[' drops
unneeded dimensions by default, this vector loses it's name. The
solution is to add 'drop = FALSE' to your subset call, like this
ldply(fits, function(x) as.data.fra
I've examining a number of linear regression models on a large dataset
following the basic ideas presented here
http://www.r-bloggers.com/r-calculating-all-possible-linear-regression-models-for-a-given-set-of-predictors/
Calculating all possible linear regressions . I run into a problem with
ldpl
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