Description Usage Arguments Details See Also Examples
trReg
fits transformation model under dependent truncation and independent censoring via a structural transformation model.
1 2 3 4 5 6 7 8 9 |
formula |
a formula expression, of the form |
data |
an optional data frame in which to interpret the variables occurring
in the |
subset |
an optional vector specifying a subset of observations to be used in the fitting process. |
tFun |
a character string specifying the transformation function or a user specified function indicating the relationship between X, T, and a.
When
|
method |
a character string specifying how the transformation parameter is estimated. The available options are |
B |
a numerical value specifies the bootstrap size for estimating the standard error.
When |
control |
a list of control parameters. The following arguments are allowed:
|
The main assumption on the structural transformation model is that it assumes there is a latent, quasi-independent truncation time that is associated with the observed dependent truncation time, the event time, and an unknown dependence parameter through a specified funciton. The structure of the transformation model is of the form:
h(U) = (1 + a)^{-1} \times (h(T) + ah(X)),
where T is the truncation time, X is the observed failure time, U is the transformed truncation time that is quasi-independent from X and h(\cdot) is a monotonic transformation function. The condition, T < X, is assumed to be satisfied. The quasi-independent truncation time, U, is obtained by inverting the test for quasi-independence by one of the following methods:
method = "kendall"
by minimizing the absolute value of the restricted inverse probability weighted Kendall's tau or maximize the corresponding p-value.
This is the same procedure used in the trSUrvfit()
function.
method = "adjust"
includes a function of latent truncation time, U, as a covariate.
A piece-wise function is constructed based on (Q + 1) indicator functions on whether U falls in the Qth and the (Q+1)th percentile,
where Q is the number of cutpoints used. See control
for details.
The transformation parameter, a, is then chosen to minimize the significance of the coefficient parameter.
1 2 3 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.