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
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 > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/Model-formula-for-ols-function-rms-package-tp3445830p3445845.html Sent from the R help mailing list archive at Nabble.com.
Thank you for your reply, Frank. %ia% drops the product x1'*x2', but
keeps x1*x2' and x1'*x2. Is there a way to drop all three of these and
include only x1*x2? Or is this not a sensible thing to want to do?
Thanks,
Mark
Frank E Harrell Jr <f.harrell at vanderbilt.edu> wrote:
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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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
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