R help - Jun 2010 - ols function in rms package

Hello,

I have a couple of questions about the ols function in Frank Harrell's rms
package.

Is there any way to specify variables by their column number in the data
frame rather than by the variable name?

For example,

library(rms)
x1 <- rnorm(100, 0, 1)
x2 <- rnorm(100, 0, 1)
x3 <- rnorm(100, 0, 1)
y <- x2 + x3 + rnorm(100, 0, 5)
d <- data.frame(x1, x2, x3, y)
rm(x1, x2, x3, y)
lm(y ~ d[,2] + d[,3], data = d)  # This works
ols(y ~ d[,2] + d[,3], data = d) # Gives error
Error in if (!length(fname) || !any(fname == zname)) { :
  missing value where TRUE/FALSE needed

However, this works:
ols(y ~ x2 + d[,3], data = d)

The reason I want to do this is to program variable selection for
bootstrap model validation.

A related question: does ols allow "y ~ ." notation?

lm(y ~ ., data = d[, 2:4])  # This works
ols(y ~ ., data = d[, 2:4]) # Gives error
Error in terms.formula(formula) : '.' in formula and no 'data'
argument

Thanks for any help you can give.

Regards,
Mark
-- 
Mark Seeto
Statistician

National Acoustic Laboratories <http://www.nal.gov.au/>
A Division of Australian Hearing

126 Greville Street
Chatswood NSW 2067 Australia
P +61 2 9412 6800
F +61 2 9411 8273

On 06/06/2010 10:49 PM, Mark Seeto wrote:
> Hello,
>
> I have a couple of questions about the ols function in Frank Harrell's
rms
> package.
>
> Is there any way to specify variables by their column number in the data
> frame rather than by the variable name?
>
> For example,
>
> library(rms)
> x1<- rnorm(100, 0, 1)
> x2<- rnorm(100, 0, 1)
> x3<- rnorm(100, 0, 1)
> y<- x2 + x3 + rnorm(100, 0, 5)
> d<- data.frame(x1, x2, x3, y)
> rm(x1, x2, x3, y)
> lm(y ~ d[,2] + d[,3], data = d)  # This works
> ols(y ~ d[,2] + d[,3], data = d) # Gives error
> Error in if (!length(fname) || !any(fname == zname)) { :
>    missing value where TRUE/FALSE needed
>
> However, this works:
> ols(y ~ x2 + d[,3], data = d)
>
> The reason I want to do this is to program variable selection for
> bootstrap model validation.
>
> A related question: does ols allow "y ~ ." notation?
>
> lm(y ~ ., data = d[, 2:4])  # This works
> ols(y ~ ., data = d[, 2:4]) # Gives error
> Error in terms.formula(formula) : '.' in formula and no
'data' argument
>
> Thanks for any help you can give.
>
> Regards,
> Mark
Hi Mark,

It appears that you answered the questions yourself.  rms wants real 
variables or transformations of them.  It makes certain assumptions 
about names of terms.   The y ~ . should work though; sometime I'll have 
a look at that.

But these are the small questions compared to what you really want.  Why 
do you need variable selection, i.e., what is wrong with having 
insignificant variables in a model?  If you indeed need variable 
selection see if backwards stepdown works for you.  It is built-in to 
rms bootstrap validation and calibration functions.

Frank

-- 
Frank E Harrell Jr   Professor and Chairman        School of Medicine
                      Department of Biostatistics   Vanderbilt University