mable.reg: Mable fit of semiparametric regression model based on...

In mable: Maximum Approximate Bernstein/Beta Likelihood Estimation

Mable fit of semiparametric regression model based on interval censored data

Description

Wrapping all mable fit of regression models in one function. Using maximum approximate Bernstein/Beta likelihood estimation to fit semiparametric regression models: Cox ph model, proportional odds(po) model, accelerated failure time model, and so on.

Usage

mable.reg(
  formula,
  data,
  model = c("ph", "aft", "po"),
  M,
  g = NULL,
  pi0 = NULL,
  tau = Inf,
  x0 = NULL,
  controls = mable.ctrl(),
  progress = TRUE
)

Arguments

formula	regression formula. Response must be of the form cbind(l, u). See 'Details'.
data	a data frame containing variables in formula.
model	the model to fit. Current options are "ph" (Cox PH) or "aft" (accelerated failure time model)
M	a vector (m0, m1) specifies the set of consective integers as candidate degrees
g	an initial guess of the regression coefficients
pi0	Initial guess of \pi(x_0) = F(\tau_n|x_0). Without right censored data, pi0 = 1. See 'Details'.
tau	right endpoint of support [0, \tau) must be greater than or equal to the maximum observed time
x0	a data frame containing working baseline covariates on the right-hand-side of formula. See 'Details'.
controls	Object of class mable.ctrl() specifying iteration limit and other control options. Default is mable.ctrl.
progress	if TRUE a text progressbar is displayed

Details

For "ph" model a missing initial guess of the regression coefficients g is obtained by ic_sp() of package icenReg. For "aft" model a missing g is imputed by the rank estimate aftsrr() of package aftgee for right-censored data. For general interval censored observations, we keep the right-censored but replace the finite interval with its midpoint and fit the data by aftsrr() as a right-censored data.

Value

A 'mable_reg' class object

Author(s)

Zhong Guan <[e-mail]>

See Also

mable.aft, mable.ph, mable.po

mable documentation built on Oct. 1, 2024, 9:06 a.m.