MIICD (version 2.4)

MIICD.coxph: Cox regression for interval censored data using multiple imputation

Description

Uses the multiple imputation approach to compute the regression coefficient and its associated variance-covariance matrix, and the baseline survival estimates of a Cox proportional hazards regression for interval censorded data

Usage

MIICD.coxph(formula, k, m, data, method = c("PMDA", "ANDA"),
  verbose = FALSE)

Arguments

formula

A formula. The right hand side indicates names of covariables to be found in data

method

Which data augmentation scheme shall be used ? Two algorithms are implemented : The Poor man's Data Augmentation scheme and the Asymptotic Normal Data Augmentation scheme (the later may be preferred).

verbose

Logical, display the results ?

k

An integer, indicates the number of iteration to perform

m

An integer, indicates the number of imputation to perform at each iteration

data

The input data (see details)

Value

est A data frame with estimates

Details

This function uses multiple imputation approach to estimate regression coefficient, its variance-covvariance matrix, and baseline survival estimates for a Cox proportional hazards regression for interval censorded data.

Estimates are computed using Rubin's rules (Rubin (1987)). Estimate of coefficient is computed as the mean of estimates over imputation. #' The variance-covariance matrix is computed as the within imputation variance and the between imputation variance augmented by an inflation factor to take into account the finite number of imputation. At each iteration, the baseline survival function is updated and multiple imputation is performed using updated estimates.

Print and plot methods are available to handle results.

The data must contain at last two columns: left and right. For interval censored data, the left and the right columns indicates lower and upper bounds of intervals respectively. Inf in the right column stands for right censored observations.

References

Delord, M. & Genin, E. Multiple Imputation for Competing Risks Regression with Interval Censored Data Journal of Statistical Computation and Simulation, 2015

PAN, Wei. A Multiple Imputation Approach to Cox Regression with Interval-Censored Data. Biometrics, 2000, vol. 56, no 1, p. 199-203.

Rubin, D. B. (1987). Multiple imputation for nonresponse in surveys.

Schenker, N. and Welsh, A. (1988). Asymptotic results for multiple imputation. The Annals of Statistics pages 1550-1566.

Tanner, M. A. and Wong, W. H. (1987). An application of imputation to an estimation problem in grouped lifetime analysis. Technometrics 29, 23-32.

Wei, G. C., & Tanner, M. A. (1991). Applications of multiple imputation to the analysis of censored regression data. Biometrics, 47(4), 1297-1309.

See Also

Surv, survfit, coxph, mvrnorm

Examples

res <- MIICD.coxph(formula = ~ treatment, k = 5, m = 5, data = bcos, verbose = FALSE)
 plot(res)
 #diagnostic plot for coefficients end associated standard error
 plot(res , type = 'coef' , coef = 1)
 plot(res , type = 'sigma' , coef = 1)