XploRe Help : kaplanmeier

Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Library:	stats
See also:	hazard

Quantlet:		kaplanmeier
Description:		Calculation of the Kaplan-Meir (product limit) estimator of the hazard rate and the survivor function for a set of durations. The first column of the input is a censorship indicator variable, (equal to zero if the duration is censored, and to one otherwise); the second column is the duration.

Reference(s):

Cox, D.R. and D. Oakes (1984): Analysis of Survival data. Chapman & Hall

Usage:	`h = kaplanmeier(y {,intervals {,disp}})`
Input:
	`y`	n x 2 matrix
	`intervals`	vector
	`disp`	constant
Output:
	`h`	vector

Note:

If no grid of intervals is provided, the macro returns in the first row the exit time, in the second row the estimated hazard rate at this time, and in the third row the estimated survivor function. If a grid of intervals is provided, this macro evaluates the hazard rate and the survivor functions by step functions on this grid, and returns in the first row the beginning of each interval, in the second row the estimated hazard for that interval, and in the third row the estimated survivor function. If a constant argument is provided, the macro plots also the estimated hazard and survivor functions. This constant argument should appear as last argument. kaplanmeier generates the grphical display.

Example:

;Nonparametric estimator of the hazard rate for the leukaemia ; data library("stats") x = read("leukaemia.dat") h = kaplanmeier(x) h

Result:

Contents of h
[1,]        6  0.14286  0.85714
[2,]        7  0.058824  0.80672
[3,]       10  0.066667  0.75294
[4,]       13  0.083333   0.6902
[5,]       16  0.090909  0.62745
[6,]       22  0.14286  0.53782
[7,]       23  0.16667  0.44818

Example:

;Nonparametric estimator of the hazard rate for the leukaemia ; data. library("stats") x = read("leukaemia.dat") h = kaplanmeier(x,1) h

Result:

Same as above. The estimated hazard rate and survivor
functions are displayed, as a constant appears as last argument.

Example:

; Nonparametric estimator of the hazard rate for the leukaemia ; data, on a grid interval. library("stats") x = read("leukaemia.dat") k = #(4,8,12,16,20,30); The grid intervals h = kaplanmeier(x,k) h

Result:

Contents of h
[1,]        4  0.42857  0.57143
[2,]        8   0.3125  0.39286
[3,]       12  0.33333   0.2619
[4,]       16  0.27273  0.19048
[5,]       20     0.25  0.14286

Example:

; Nonparametric estimator of the hazard rate for the leukaemia ; data, on a grid interval. library("stats") x = read("leukaemia.dat") k = #(4,8,12,16,20) h = kaplanmeier(x,k,2) h

Result:

Same as above. The estimated hazard rate and survivor
functions are displayed, as a constant appears as last argument.

Author: G. Teyssiere, 19980530 license MD*Tech