For the mean() example, I believe this should work (untested)
for (var in names(Dataset)) print( mean( Dataset[[var]] , na.rm=TRUE ) )
or
for (var in names(Dataset)) print( mean( Dataset[,var] , na.rm=TRUE ) )
But it's harder with lm, glm, and friends. For them I think maybe you
can do it by constructing a formula object, see ?formula.
Maybe something like,
tmpf <- as.formula( paste( var, ' ~var1 + var2 + var3') )
glm( tmpf , Dataset)
inside the loop, but I haven't done this and am not an expert.
Here's a quick example:
foo <- data.frame( x=1:10, y=rnorm(10) )
ick <- as.formula( ' x ~ y')
lm(ick,foo)
Call:
lm(formula = ick, data = foo)
Coefficients:
(Intercept) y
5.895 2.158
## compare with:
lm(x~y,foo)
Call:
lm(formula = x ~ y, data = foo)
Coefficients:
(Intercept) y
5.895 2.158
But it's a question that comes up periodically on r-help, so I'd also
suggest searching the archives.
-Don
At 10:50 AM -0400 6/18/09, Jon Erik Ween wrote:
Hi!
I have a dataset with some 300+ variables and 2000+ records. I'd like to grind
through a bunch of analyses on the variables by using a script, but can't
figure out how to refer to variable names properly. For some of the simpler
stuff I use various "apply" functions, but for others (like t-tests
etc) I need
by command procedures. I've tried various flavors of "for(var in
names(Dataset)){...}" but this does not work consistently. Actually, "for(var
in names(Dataset){print var}, seems to work perfectly, giving a list of
variable names, but "for(var in names(Dataset)){mean(var, na.rm=T) or for(var
in names(Dataset)){glm(var~var1+var2+var3....} do not.
Any suggestions about how best to go about this?
Thanks
Jon
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--
--------------------------------------
Don MacQueen
Environmental Protection Department
Lawrence Livermore National Laboratory
Livermore, CA, USA
925-423-1062
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