Gee, so much excitement over such a little thing.
So how exactly would you prefer lm() to tell you
what levels of your factors are being taken as the
reference levels?
Post-processing, if necessary, would seem to be
pretty trivial.
If you want to re-run lm() on modified sets of
predictors, what's wrong with editing the lm(...)
command or using update()?
-Peter Ehlers
Idgarad wrote:
How for the love of god can I prevent the lm() function from padding on to
my factor variables?
I start out with 2 tables:
Table1
123123
124351
...
626773
Table2
Count,IS_DEAD,IS_BURNING
1231,T,F
4521,F,T
...
3321,T,T
Everything looks fine when I import the data.
then we get a
oh_crap <- lm(table1 ~ Count + IS_DEAD + IS_BURNING, table2)
Magically when I look at my oh_crap coefficents they get turned into
Count, IS_DEADTRUE, IS_BURNINGTRUE
I get it that it finds them to be factors by how in the name of all that is
holy do I prevent them from doing that crap since later after a stepwise
removal I go into one of the models grab what coefficents were kept
(IS_BURNINGTTRUE now) and read future regressors from the original table
which read IS_BURNING rather then IS_BURNINGTRUE.
Since there is a mix of numeric and dummy regressors I cannot selectively
append TRUE to variables names as I don't have control of what regressors
get imported (one month there might be 50 and another month 2).
How can I stop lm() from padding onto a coefficent's name?
I have no objection to post processing by finding and assasinating any name
with the word TRUE appended to the end of a name but in that case then how
do I change the coeff name?
Maddening... who thought it would be a good idea to append things without
asking? A simple lm(appendFactor=FALSE) would have been nice... took me 3
hours to find out what was going wrong on this.... Grabbing coffee, a carton
of cigs, and heading outside to smash my head with a brick to make the
hurting stop....
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--
Peter Ehlers
University of Calgary
403.202.3921
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