Dimitri -
   Without commenting on the wiseness of such an approach,
here's one way to do what you want:

regs = lapply(predictors,function(var)lm(data$y~data[,var]))
names(regs) = predictors

Now

regs[['x1']] holds the lm output from the regression of y on x1,
regs[['x2']] holds the lm output from the regression of y on x2, etc.

Suppose you wanted to know what the slopes for each regressor were.
First, find what you want for one:

coef(regs[['x1']])[2]

Next, write a function to extract this information:

getslope = function(reg)coef(reg)[2]

Now use sapply to get all the slopes of the individual regressions:

sapply(regs,getslope)

Hope this helps.

                                        - Phil Spector
                                         Statistical Computing Facility
                                         Department of Statistics
                                         UC Berkeley
                                         spec...@stat.berkeley.edu




On Tue, 9 Mar 2010, Dimitri Liakhovitski wrote:

Dear R-ers,
I have a data frame data with predictors x1 through x5 and the
response variable y.
I am running a simple regression:

reg<-lm(y~x1, data=data)

I would like to loop through all predictors. Something like:
predictors<-c("x1","x2",... "x10)
for(i in predictors){
 reg<-lm(y~i)
etc.
}

But it's not working. I am getting an error:
Error in model.frame.default(formula = Y ~ x1 + x2 + x3 + i, data = sample,  :
 variable lengths differ (found for 'i')

How can I make it take predictor names in the lm formula?
Thank you!

--
Dimitri Liakhovitski
Ninah.com
dimitri.liakhovit...@ninah.com

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