mets (version 1.3.11)

gofZ_phreg: Goodness-of-Fit for Cox Covariates (Linearity)

Description

Tests the functional form of continuous covariates in a Cox PH model to check for linearity. It computes cumulative residuals evaluated at a grid of covariate values \(z\).

Usage

gofZ_phreg(
  formula,
  data,
  vars = NULL,
  offset = NULL,
  weights = NULL,
  breaks = 50,
  equi = FALSE,
  n.sim = 1000,
  silent = 1,
  ...
)

Value

An object of class "gof.phreg" with type "Zmodelmatrix" containing:

res

Matrix of p-values for each tested variable.

Zres

List of gof.phreg objects, one for each variable.

type

Type of test ("Zmodelmatrix").

Arguments

formula

Formula for the Cox regression.

data

Data frame.

vars

Vector of variable names to test. If NULL, automatically detects continuous covariates with more than 2 levels.

offset

Offset vector.

weights

Weights vector.

breaks

Number of break points for the grid (default 50).

equi

Logical; if TRUE, uses equidistant breaks; if FALSE, uses quantiles.

n.sim

Number of simulations (default 1000).

silent

Logical; suppresses timing estimates.

...

Additional arguments passed to gofM_phreg.

Author

Thomas Scheike and Klaus K. Holst

Details

The test statistic is: $$ U(z, \tau) = \int_0^\tau K(z)^T d \hat M $$ where \(K(z)\) is a design matrix based on indicator functions \(I(Z_i \leq z_l)\) for a grid of points \(z_l\).

The p-value is valid but depends on the chosen grid. As the number of break points increases, this test converges to the original Lin, Wei, and Ying test for linearity.

See Also

gofM_phreg, cumContr

Examples

data(TRACE)
set.seed(1)
TRACEsam <- blocksample(TRACE, idvar="id", replace=FALSE, 100)

## Test linearity of continuous covariates
 ## Reduce Ex.Timings
m1 <- gofZ_phreg(Surv(time,status==9)~strata(vf)+chf+wmi+age, data=TRACEsam)
summary(m1) 
plot(m1, type="z")