Function
Compose an S Function to Compute X beta from a Fit
Function
is a class of functions for creating other S functions.
Function.rms
is the method for creating S functions to compute
X beta, based on a model fitted with rms
in effect.
Like latexrms
, Function.rms
simplifies restricted cubic
spline functions and factors out terms in second-order interactions.
Function.rms
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.
perlcode
similarly creates Perl code to evaluate a fitted
regression model.
Usage
# S3 method for rms
Function(object, intercept=NULL,
digits=max(8, .Options$digits), …)
# S3 method for cph
Function(object, intercept=-object$center, …)# Use result as fun(predictor1=value1, predictor2=value2, \dots)
sascode(object, file='', append=FALSE)
perlcode(object)
Arguments
- object
a fit created with
rms
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 havesascode
append code to an existing file namedfile
.- …
arguments to pass to
Function.rms
fromFunction.cph
Value
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.
perlcode
returns a character string with embedded newline characters.
See Also
Examples
# NOT RUN {
suppressWarnings(RNGversion("3.5.0"))
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)
cat(perlcode(g), '\n')
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'))
# }