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. |
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 |