Obtain standard errors of regression coefficients for an “mlm” object returned by `lm()`

Question

I\'d like to run 10 regressions against the same regressor, then pull all the standard errors without using a loop.

depVars <- as.matrix(         


        

Answer 1

Here an option:

1. put your data in the long format using regressor as an id key.
2. do your regression against value by group of variable.

For example , using mtcars data set:

library(reshape2)
dat.m <- melt(mtcars,id.vars='mpg')  ## mpg is my regressor
library(plyr)
ddply(dat.m,.(variable),function(x)coef(lm(variable~value,data=x)))
  variable (Intercept)         value
1       cyl           1  8.336774e-18
2      disp           1  6.529223e-19
3        hp           1  1.106781e-18
4      drat           1 -1.505237e-16
5        wt           1  8.846955e-17
6      qsec           1  6.167713e-17
7        vs           1  2.442366e-16
8        am           1 -3.381738e-16
9      gear           1 -8.141220e-17
10     carb           1 -6.455094e-17