bssmle_lt | R Documentation |
Routine that performs B-spline sieve maximum likelihood estimation with linear and nonlinear inequality/equality constraints
bssmle_lt(formula, data, alpha, k = 1)
formula |
a formula object relating survival object |
data |
a data frame that includes the variables named in the formula argument |
alpha |
α = (α1, α2) contains parameters that define the link functions from class of generalized odds-rate transformation models. The components α1 and α2 should both be ≥ 0. If α1 = 0, the user assumes the proportional subdistribution hazards model or the Fine-Gray model for the event type 1. If α2 = 1, the user assumes the proportional odds model for the event type 2. |
k |
a parameter that controls the number of knots in the B-spline with 0.5 ≤ |
The function bssmle_lt
performs B-spline sieve maximum likelihood estimation for left-truncated and interval-censored competing risks data.
The function bssmle_lt
returns a list of components:
beta |
a vector of the estimated coefficients |
varnames |
a vector containing variable names |
alpha |
a vector of the link function parameters |
loglikelihood |
a loglikelihood of the fitted model |
convergence |
an indicator of convegence |
tms |
a vector of the minimum and maximum observation times |
Z |
a design matrix |
Tw |
a vector of |
Tv |
a vector of |
Tu |
a vector of |
Bw |
a list containing the B-splines basis functions evaluated at |
Bv |
a list containing the B-splines basis functions evaluated at |
Bu |
a list containing the B-splines basis functions evaluated at |
dBw |
a list containing the first derivative of the B-splines basis functions evaluated at |
dBv |
a list containing the first derivative of the B-splines basis functions evaluated at |
dBu |
a list containing the first derivative of the B-splines basis functions evaluated at |
dmat |
a matrix of event indicator functions |
Jun Park, jun.park@alumni.iu.edu
Giorgos Bakoyannis, gbakogia@iu.edu
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