icenReg (version 1.3.5)

ic_np: Non-Parametric Estimator for Interval Censored Data

Description

Fits the non-parametric maximum likelihood estimator (NPMLE) for univariate interval censored data. This is a generalization of the Kaplan-Meier curves that allows for interval censoring. Also referred to as the Turnbull estimator.

Usage

ic_np(formula = NULL, data, maxIter = 1000, tol = 10^-10)

Arguments

formula

formula for stratification. If only one group, can be left blank and data must be entered as n x 2 matrix.

data

a n x 2 matrix or dataframe. See details.

maxIter

maximum iterations

tol

numeric tolerance

Details

data must be an n x 2 matrix or data.frame containing two columns of data representing left and right sides of the censoring interval, denoted L and R. This allows for left censored (L == 0), right censored (R == inf), uncensored (L == R) along with general interval censored observations. The NPMLE is fit using an efficient implementation of the EMICM algorithm.

References

Turnbull, B. (1976) The empricial distribution with arbitrarily grouped and censored data, Journal of the Royal Statistical Society B, vol 38 p290-295

Wellner, J. A., and Zhan, Y. (1997) A hybrid algorithm for computation of the maximum likelihood estimator from censored data, Journal of the American Statistical Association, Vol 92, pp945-959 Anderson-Bergman, C. (preprint) An efficient implementation of the EMICM algorithm for the interval censored NPMLE

Examples

  data(IR_diabetes)

  fit <- ic_np(cbind(left, right) ~ gender,
               data = IR_diabetes)  

  # Stratifies by gender
  # If only one group, okay to enter data as n x 2 matrix
  
  plot(fit, col = c('blue', 'orange') )