testCox: Test the Cox model computation for the TBF approach

In glmBfp: Bayesian Fractional Polynomials for GLMs

Description

Test the Cox model computation for the TBF approach

Usage

testCox(survTimes, censInd, offsets = rep.int(0, length(survTimes)), X,
  useCppCode = FALSE)

Arguments

survTimes	the survival times
censInd	the logical censoring indicator (TRUE = observed, FALSE = censored survival times)
offsets	known component to be included in the linear predictor during fitting. This must be a numeric vector of length equal to the number of cases (if not provided, a vector of zeroes)
X	the design matrix, *without* the intercept 1's!, with at least one column
useCppCode	use the C++ code? (default) otherwise the R-function coxph is used

Value

a list with the coefficient estimates (betas), the covariance matrix estimate (cov) and the residual deviance (deviance).

Author(s)

Daniel Sabanes Bove

glmBfp documentation built on May 2, 2019, 5:26 p.m.