prior_pred {survextrap} | R Documentation |
Simulate a dataset from the prior predictive distribution of survival times in an M-spline survival model.
Description
Simulate a dataset from the prior predictive distribution of survival times in an M-spline survival model. Additive hazards models not currently supported.
Usage
prior_pred(
n,
fix_prior = FALSE,
mspline,
censtime = Inf,
coefs_mean = NULL,
prior_hscale = p_normal(0, 20),
prior_hsd = p_gamma(2, 1),
newdata = NULL,
formula = NULL,
prior_loghr = NULL,
prior_hrsd = NULL,
prior_cure = NULL
)
Arguments
n |
Sample size of the simulated dataset. Each observation in the dataset is generated from a model with the same parameters. These parameters are generated from a single simulation from the prior distribution. |
fix_prior |
If |
mspline |
A list of control parameters defining the spline model.
If there are external data, and both
|
censtime |
Right-censoring time to impose on the simulated event times. |
coefs_mean |
Spline basis coefficients that define the prior
mean for the hazard function. By default, these are set to values
that define a constant hazard function (see
|
prior_hscale |
Prior for the baseline log hazard scale
parameter ( Note that "Baseline" is defined by the continuous covariates taking a value of zero and factor covariates taking their reference level. To use a different baseline, the data should be transformed appropriately beforehand, so that a value of zero has a different meaning. For continuous covariates, it helps for both computation and interpretation to define the value of zero to denote a typical value in the data, e.g. the mean. |
prior_hsd |
Gamma prior for the standard deviation that
controls the variability over time (or smoothness) of the hazard
function. This should be a call to |
newdata |
A data frame with one row, containing variables in the model formulae. Samples will then be drawn, for any covariate-dependent parameters, with covariates set to the values given here. |
formula |
A model formula with no response, defining the covariates on the hazard scale. |
prior_loghr |
Priors for log hazard ratios. This should be a
call to The default is |
prior_hrsd |
Prior for the standard deviation parameters that
smooth the non-proportionality effects over time in
non-proportional hazards models. This should be a call to
|
prior_cure |
Prior for the baseline cure probability. This should be a
call to |
Value
A data frame with columns time
(simulated time) and
event
(indicator for whether the time is an event time, as
opposed to a right-censoring time). The prior parameters are
returned in the prior
attribute as a list with components
alpha
(baseline log hazard) and coefs
(spline
coefficients).