[R] Model formula for ols function (rms package)

[Frank Harrell]

For the first example you want the restricted interaction operator: y ~
rcs(x1, 3) + rcs(x2, 3) + rcs(x1, 3) %ia% rcs(x2, 3).

For the second example use pol(x,2) or something like pol(x1,2) + pol(x2,2)
+ pol(x1, 2) %ia% pol(x2, 2)

If you have to create new variables for R formulas you're usually doing
something wrong.
Frank


Mark Seeto wrote:
> 
> Dear R help,
> 
> I'm having some trouble with model formulas for the ols function in
> the rms package. I want to have two variables represented as
> restricted cubic splines, and also include an interaction as a product
> of linear terms, but I get an error message.
> 
> library(rms)
> d <- data.frame(x1 = rnorm(50), x2 = rnorm(50), y = rnorm(50))
> 
> ols(y ~ rcs(x1,3) + rcs(x2,3) + x1*x2, data=d)
> Error in if (!length(fname) || !any(fname == zname)) { :
>   missing value where TRUE/FALSE needed
> 
> ols(y ~ rcs(x1,3) + rcs(x2,3) + I(x1*x2), data=d)
> Error in if (!length(fname) || !any(fname == zname)) { :
>   missing value where TRUE/FALSE needed
> 
> I get the same error if I try to fit a model with a quadratic term:
> 
> ols(y ~ x1 + I(x1^2), data=d)
> Error in if (!length(fname) || !any(fname == zname)) { :
>   missing value where TRUE/FALSE needed
> 
> ols(y ~ I(x1^2), data=d)  # No error message, but lacks linear term
> 
> Is there a way to do these things without first creating new variables
> in the data frame?
> 
> Thanks,
> 
> Mark Seeto
> National Acoustic Laboratories
> 
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> 


-----
Frank Harrell
Department of Biostatistics, Vanderbilt University
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