| Library: | hazreg |
| See also: | hazdat hazregll hazbeta hazbase |
| 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, 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. | |
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
The conditional survival function is estimated.
| Library: | hazreg |
| See also: | hazdat hazregll hazbeta hazbase |