TPreg {idmTPreg} | R Documentation |
Fits a semi-parametric regression model to estimate the effects on transition probabilities in a (possibly non-Markov) progressive illness-death model for a sequence of time.
TPreg(formula, data, link, s = 0, t = NULL, R = 199, by = NULL, trans, ncores = NULL)
formula |
an object of class formula which specifies the covariates. For example
|
data |
a data.frame of |
link |
a link function for |
s |
the current time for the transition probabilities; default is zero which reports the occupation probabilities. |
t |
the Future time for the transition probabilities; default is |
R |
the number of bootstrap replicates. Default is 199. |
by |
number: increment of the sequence from time |
trans |
the possible transition(s) for a progressive illness-death model. For |
ncores |
the number of cores to use for parallel execution. Default is the number of CPU cores on the current host. |
TPreg
returns an object of class TPreg
.
An object of class TPreg
is a list containing at least the following components:
co |
the list of:
|
call |
the matched call. |
transition |
the transition, this is equal to the |
s |
the current time for the transition probability. |
t |
the future time for the transition probability. |
n.misobs |
the number of missing observations. |
In addition, trans="all"
will have four lists: co11
, co12
, co13
, and co23
instead of co
and will give the information for all possible transitions in the progressive illness death model
Azarang, L. Scheike, TH. and de Una-Alvarez, J. (2017) Direct modeling of regression effects for transition probabilities in the progressive illness-death model, Statistics in Medicine 36, 1964-1976.
print.TPreg
, summary.TPreg
, and plot.TPreg
as generic functions.
data(colonTPreg) co11 <- TPreg( ~ Age + Nodes + treatment, colonTPreg, link = "logit", s = 50, R = 19, t = 200, trans = "11", ncores = 1) co11 summary(co11)