| 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. | |
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
The conditional survival function is estimated.