calc_risk_term: Calculate absolute risk profiles after non-terminal event

In hreed7/SemiCompRisksPen: Penalized Models for Semi-Competing Risks

Calculate absolute risk profiles after non-terminal event

Description

This function calculates absolute risk profiles conditional on non-terminal event already occurring.

Usage

calc_risk_term(
  para,
  Xmat3,
  hazard,
  knots_list = NULL,
  t_cutoff,
  t_start,
  tol = 0.001,
  frailty = TRUE,
  type = "marginal",
  gamma = 1,
  model = "semi-markov",
  h3_tv = "none",
  tv_knots = NULL
)

Arguments

para	A numeric vector of parameters, arranged as follows: the first k_1+k_2+k_3 elements correspond to the baseline hazard parameters, then the k_1+k_2+k_3+1 element corresponds to the gamma frailty log-variance parameter, then the lastq_1+q_2+q_3 elements correspond with the regression parameters.
Xmat3	Numeric matrices with n rows and q_1,q_2,q_3 columns containing covariates.
hazard	String specifying the form of the baseline hazard.
knots_list	Used for hazard specifications besides Weibull, a list of three increasing sequences of integers, each corresponding to the knots for the flexible model on the corresponding transition baseline hazard. If NULL, will be created by get_default_knots_list.
t_cutoff	Numeric vector indicating the time(s) to compute the risk profile.
t_start	Numeric scalar indicating the dynamic start time to compute the risk profile. Set to 0 by default.
tol	Numeric value for the tolerance of the numerical integration procedure.
frailty	Boolean indicating whether a gamma distributed subject-specific frailty should be included. Currently this must be set to TRUE.
type	String either indicating 'marginal' for population-averaged probabilities, or 'conditional' for probabilities computed at the specified gamma
gamma	Numeric value indicating the fixed level of the frailty assumed for predicted probabilities, if 'type' is set to 'conditional'
model	String specifying the transition assumption
h3_tv	String indicating whether there is an effect of t1 on hazard 3.
tv_knots	for piecewise effect of t1 in h3, these are the knots at which the effect jumps

Value

if Xmat has only one row, and t_cutoff is a scalar, then returns a 4 element row matrix of probabilities. If Xmat has n rows, then returns an n by 4 matrix of probabilities. If Xmat has n rows and t_cutoff is a vector of length s, then returns an s by 4 by n array.

hreed7/SemiCompRisksPen documentation built on Dec. 15, 2024, 5:41 p.m.