| finda {hds} | R Documentation |
Estimate the time-varying coefficients from a local-in-time Cox model
Description
finda estimates the time-varying coefficients beta(t) at a single time
from a local-in-time Cox model. Think of it as a Cox model where the
the coefficients are allowed to vary with time. Further details can be found
in Cai and Sun (2003) and Tian et al. (2005).
Usage
finda(tt, times, status, covars, start = rep(0, ncol(covars)), h = 400, ...)
Arguments
tt |
Time to estimate beta(t) at |
times |
A vector of observed follow up times. |
status |
A vector of status indicators, usually 0=alive, 1=dead. |
covars |
A matrix or data frame of numeric covariate values, with a column for each covariate and each observation is on a separate row. |
start |
A vector of length p of starting values to be passed to
|
h |
A single value on the time scale representing the bandwidth to use. |
... |
Additional parameters to pass to |
Details
The naming of the function finda stands for "find a(t)", where "a(t)"
is the notation used in Cai and Sun (2003) to represent the time-varying
Cox model coefficients. We also refer to "a(t)" as "beta(t)" through the documentation.
The user typically will not interact with this function, as finda is
wrapped by hdslc.
Value
A vector of length p, where p is the number of covariates. The vector
is the estimated beta(t) from the local-in-time Cox model at time tt.
References
Cai Z and Sun Y (2003). Local linear estimation for time-dependent coefficients in Cox's regression models. Scandinavian Journal of Statistics, 30: 93-111. doi:10.1111/1467-9469.00320
Tian L, Zucker D, and Wei LJ (2005). On the Cox model with time-varying regression coefficients. Journal of the American Statistical Association, 100(469):172-83. doi:10.1198/016214504000000845