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Last data update: 2014.03.03

R: Compares different scores in different regression objects.

forestplotCombineRegrObj

R Documentation

Compares different scores in different regression objects.

Description

Creates a composite from different regression objects into one forestplot where you can choose the variables of interest to get an overview and easier comparison.

Usage

forestplotCombineRegrObj(regr.obj, variablesOfInterest.regexp, reference.names,
  rowname.fn, estimate.txt, exp = xlog, add_first_as_ref = FALSE,
  ref_txt = "ref.", ref_labels = c(), digits = 1, is.summary, xlab, zero,
  xlog, ...)

Arguments

`regr.obj`	A list with all the fits that have variables that are to be identified through the regular expression
`variablesOfInterest.regexp`	A regular expression identifying the variables that are of interest of comparing. For instance it can be "(score\|index\|measure)" that finds scores in different models that should be compared.
`reference.names`	Additional reference names to be added to each model
`rowname.fn`	A function that takes a rowname and sees if it needs beautifying. The function has only one parameter the coefficients name and should return a string or expression.
`estimate.txt`	The text of the estimate, usually HR for hazard ratio, OR for odds ratio
`exp`	Report in exponential form. Default true since the function was built for use with survival models.
`add_first_as_ref`	If you want that the first variable should be reference for that group of variables. The ref is a variable with the estimate 1 or 0 depending if exp() and the confidence interval 0.
`ref_txt`	Text instead of estimate number
`ref_labels`	If add_first_as_ref is TRUE then this vector is used for the model fits.
`digits`	Number of digits to use for the estimate output
`is.summary`	A vector indicating by `TRUE`/`FALSE` if the value is a summary value which means that it will have a different font-style
`xlab`	x-axis label
`zero`	Indicates what is zero effect. For survival/logistic fits the zero is 1 while in most other cases it's 0.
`xlog`	If TRUE, x-axis tick marks are to follow a logarithmic scale, e.g. for logistic regressoin (OR), survival estimates (HR), poisson regression etc. Note: This is an intentional break with the original `forestplot` function as I've found that exponentiated ticks/clips/zero effect are more difficult to for non-statisticians and there are sometimes issues with rounding the tick marks properly.
`...`	Passed to `forestplot`

Examples

org.par <- par("ask" = TRUE)

# simulated data to test 
set.seed(10)
ftime <- rexp(200)
fstatus <- sample(0:1,200,replace=TRUE)
cov <- data.frame(
  x1 = runif(200),
  x2 = runif(200),
  x3 = runif(200))

library(rms)
ddist <- datadist(cov)
options(datadist = "ddist")

fit1 <- cph(Surv(ftime, fstatus) ~ x1 + x2, data=cov)
fit2 <- cph(Surv(ftime, fstatus) ~ x1 + x3, data=cov)

forestplotCombineRegrObj (
  regr.obj = list(fit1, fit2),
  variablesOfInterest.regexp = "(x2|x3)",
  reference.names = c("First model", "Second model"),
  new_page = TRUE)

modifyNameFunction <- function(x){
  if (x == "x1")
    return ("Covariate A")
  
  if (x == "x2")
    return (expression(paste("My ", beta[2])))
  
  return (x)
}

forestplotCombineRegrObj (
  regr.obj = list(fit1, fit2),
  variablesOfInterest.regexp = "(x2|x3)",
  reference.names = c("First model", "Second model"),
  rowname.fn = modifyNameFunction,
  new_page = TRUE)

par(org.par)

Results