| Function {Design} | R Documentation |
Function is a class of functions for creating other S functions.
Function.Design is the method for creating S functions to compute
X beta, based on a model fitted with Design in effect.
Like latex.Design, Function.Design simplifies restricted cubic
spline functions and factors out terms in second-order interactions.
Function.Design will not work for models that have third-order
interactions involving restricted cubic splines.
Function.cph is a particular method for handling fits from cph, for
which an intercept (the negative of the centering constant) is added to
the model. sascode is a function that takes an S function such
as one created by Function and does most of the editing
to turn the function definition into
a fragment of SAS code for computing X beta from the fitted model, along
with assignment statements that initialize predictors to reference values.
## S3 method for class 'Design': Function(object, intercept=NULL, digits=max(8, .Options$digits), ...) ## S3 method for class 'cph': Function(object, intercept=-object$center, ...) # Use result as fun(predictor1=value1, predictor2=value2, ...) sascode(object, file='', append=FALSE)
object |
a fit created with Design in effect
|
intercept |
an intercept value to use (not allowed to be specified to Function.cph).
The intercept is usually retrieved from the regression coefficients
automatically.
|
digits |
number of significant digits to use for coefficients and knot locations |
file |
name of a file in which to write the SAS code. Default is to write to standard output. |
append |
set to TRUE to have sascode append code to an existing file named
file.
|
... |
arguments to pass to Function.Design from
Function.cph |
Function returns an S-Plus function that can be invoked in any
usual context. The function has one argument per predictor variable,
and the default values of the predictors are set to adjust-to values
(see datadist). Multiple predicted X beta values may be calculated
by specifying vectors as arguments to the created function.
All non-scalar argument values must have the same length.
Frank Harrell
Department of Biostatistics
Vanderbilt University
f.harrell@vanderbilt.edu
latex.Design, Function.transcan, predict.Design, Design, Design.trans
set.seed(1331)
x1 <- exp(rnorm(100))
x2 <- factor(sample(c('a','b'),100,rep=TRUE))
dd <- datadist(x1, x2)
options(datadist='dd')
y <- log(x1)^2+log(x1)*(x2=='b')+rnorm(100)/4
f <- ols(y ~ pol(log(x1),2)*x2)
f$coef
g <- Function(f, digits=5)
g
sascode(g)
g()
g(x1=c(2,3), x2='b') #could omit x2 since b is default category
predict(f, expand.grid(x1=c(2,3),x2='b'))
g8 <- Function(f) # default is 8 sig. digits
g8(x1=c(2,3), x2='b')
options(datadist=NULL)
## Not run:
# Make self-contained functions for computing survival probabilities
# using a log-normal regression
f <- psm(Surv(d.time, death) ~ rcs(age,4)*sex, dist='gaussian')
g <- Function(f)
surv <- Survival(f)
# Compute 2 and 5-year survival estimates for 50 year old male
surv(c(2,5), g(age=50, sex='male'))
## End(Not run)