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 hazcoxb

Quantlet: 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, column 1: the sorted observed survival time t, column 2: the cosorted censoring indicator delta, column 3: labels l, column 4: number of ties at time t[i], cosorted, columns 5 to p+4: the cosorted covariate matrix z.
z p x 1 matrix, the covariate values for which the conditional survival curve is estimated.
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 = uniform(n,p) - 0.5          ; 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 = 0.1|0.3

surv = hazsurv(data, z1)  

; estimation of the

; conditional survival

; function                              

Result:

The conditional survival function is estimated. 


Library: hazreg
See also: hazdat hazregll hazbeta hazcoxb

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 000308
(C) MD*TECH Method and Data Technologies, 21.9.2000