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: hazreg
See also: hazdat hazregll hazbeta hazbase

Macro: hazsurv
Description: calculates the conditional survival function, using the maximum likelihood estimate of the regression parameter beta obatined through hazbeta.

Usage: surv = hazsurv(data,z)
Input:
data n x (p+4) matrix, the first column is the sorted survival time t, followed by the sorted delta, inidcating if censoring has occured, labels l, a column containing the number of ties, and lastly, the sorted covariate matrix.
z n x p matrix, the covariates.
Output:
surv n x 2 matrix, the first column is the sorted t, followed by the estimated survival function at the points of t, conditional on z.

Example:
library("hazreg") 
n = 20
p = 2
beta = 1|2                      ; regression parameter
z = 1 + uniform(n,p)            ; covariates
y = -log(1-uniform(n))          ; exponential survival
y = y./exp(z*beta)              ; covariate effects
c = 4*uniform(n)                ; uniform censoring
t = min(y~c,2)                  ; censored time             
delta = (y<=c)                  ; censoring indicator            
{data,ties} = hazdat(t,delta, z)   ; preparing data
z1 = 1.1|1.23
surv = hazsurv(data, z1)  
; estimation of the
; conditional survival
; function                              
Result:
The conditional survival function is estimated. 

Library: hazreg
See also: hazdat hazregll hazbeta hazbase

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

Author: Lijian Yang 990706
(C) MD*TECH Method and Data Technologies, 17.8.2000