Description Usage Arguments Details Value References
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).
1 |
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 |
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
.
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
.
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
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