best_cut: Find the best cutpoint for a covariate
In TalhoukLab/biostatUtil: Utility Functions Used in Biostatistics Projects

best_cut

R Documentation

Find the best cutpoint for a covariate

Description

Repeatedly finds cutpoints for an explanatory variable in a univariable Cox PH model. Also plots survival curves for each cutpoint.

Usage

best_cut(
  f,
  d,
  n = c("b", "t", "qd", "qn"),
  AIC.range = 3,
  nround = 3,
  plot = TRUE,
  filename = NULL,
  nrow = NULL,
  ncol = NULL,
  title = "",
  ...
)

Arguments

`f`	formula object
`d`	data frame
`n`	number of groups to transform variable into. Options are "b" (two), "t" (three), "qd" (four), and "qn" (five)
`AIC.range`	If range of AIC is within `AIC.range` units, the likelihood is too flat. We choose the best cutpoint using the alternative method.
`nround`	number of digits to round AIC and p-value on plots
`plot`	logical; If `TRUE`, shows the survival curves for each cutpoint in a facetted figure
`filename`	file name for saving a png image of figure
`nrow`	number of rows in facetted plot
`ncol`	number of columns in facetted plot
`title`	title for plot
`...`	additional arguments for `plot`

Details

Takes the cutpoint resulting in the lowest AIC. If the range of AIC values is within AIC.range units, take the cutpoint that results in the two groups having the most similar numbers of events and cases. The function can cut a variable into anywhere from 2 to 5 groups.

Value

A list with the following elements

`cuts`	vector of cutpoints considered
`fits`	A list of `coxph` objects run for each cutpoint
`results`	A table showing the likelihood ratio test p-value, log likelihood, and AIC for each cutpoint
`opt.cut`	optimal cutpoint value
`flat.lik`	If `TRUE`, the likelihood was too flat and the alternative method was used