Function function

Compose an S Function to Compute X beta from a Fit

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.

## S3 method for class 'rms' Function(object, intercept=NULL, digits=max(8, .Options$digits), posterior.summary=c('mean', 'median', 'mode'), ...) ## S3 method for class 'cph' Function(object, intercept=-object$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
  • posterior.summary: if using a Bayesian model fit such as from blrm, specifies whether to use posterior mode/mean/median parameter estimates in generating the function
  • 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.rms from Function.cph

Returns

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.

Author(s)

Frank Harrell, Jeremy Stephens, and Thomas Dupont

Department of Biostatistics

Vanderbilt University

fh@fharrell.com

See Also

latexrms, transcan, predict.rms, rms, rms.trans

Examples

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: require(survival) # 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)
  • Maintainer: Frank E Harrell Jr
  • License: GPL (>= 2)
  • Last published: 2025-01-17