# [R] looping through predictors

Phil Spector spector at stat.berkeley.edu
Wed Mar 10 00:35:03 CET 2010

```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']])

Next, write a function to extract this information:

getslope = function(reg)coef(reg)

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
spector at 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.Liakhovitski at ninah.com
>
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