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Creating data frame with residuals of a data frame

2 messages · francesca casalino, jim holtman

francesca casalino
# 
Dear experts,

I am trying to create a data frame from the residuals I get after
having applied a linear regression to each column of a data frame, but
I don't know how to create this data frame from the resulting list
since the list has differing numbers of rows.

So for example:
age<- c(5,6,10,14,16,NA,18)
value1<- c(30,70,40,50,NA,NA,NA)
value2<- c(2,4,1,4,4,4,4)
df<- data.frame(age, value1, value2)

#Run linear regression to adjust for age and get residuals:

lm_f <- function(x) {
x<- residuals(lm(data=df, formula= x ~ age))
}
resid <- apply(df,2,lm_f)
resid<- resid[-1]

Then resid is a list with different row numbers:

$value1
         1          2          3          4
-16.945813  22.906404  -7.684729   1.724138

$value2
          1           2           3           4           5           7
-0.37398374  1.50406504 -1.98373984  0.52845528  0.28455285  0.04065041

I am trying to get both the original variable and their residuals in
the same data frame like this:

age, value1, value2, resid_value1, resid_value2

But when I try cbind or other operations I get an error message
because they do not have the same number of rows. Can you please help
me figure out how to solve this?

Thank you.
2 days later
jim holtman
# 
try this:
+ x<- residuals(lm(data=df, formula= x ~ age))
+ }
+     newCol <- paste(i, 'res', sep = '')
+     df[[newCol]] <- NA  # initialize
+     df[[newCol]][as.integer(names(resid[[i]]))] <- resid[[i]]
+ }
age value1 value2  value1res   value2res
1   5     30      2 -16.945813 -0.37398374
2   6     70      4  22.906404  1.50406504
3  10     40      1  -7.684729 -1.98373984
4  14     50      4   1.724138  0.52845528
5  16     NA      4         NA  0.28455285
6  NA     NA      4         NA          NA
7  18     NA      4         NA  0.04065041


On Mon, Oct 24, 2011 at 10:23 AM, francesca casalino
<francy.casalino at gmail.com> wrote: