hare: Hare: hazard regression

In polspline: Polynomial Spline Routines

Hare: hazard regression

Description

Fit a hazard regression model: linear splines are used to model the baseline hazard, covariates, and interactions. Fitted models can be, but do not need to be, proportional hazards models.

Usage

hare(data, delta, cov, penalty, maxdim, exclude, include, prophaz = FALSE,
additive = FALSE, linear, fit, silent = TRUE) 

Arguments

data	vector of observations. Observations may or may not be right censored. All observations should be nonnegative.
delta	binary vector with the same length as data. Elements of data for which the corresponding element of delta is 0 are assumed to be right censored, elements of data for which the corresponding element of delta is 1 are assumed to be uncensored. If delta is missing, all observations are assumed to be uncensored.
cov	covariates: matrix with as many rows as the length of data. May be omitted if there are no covariates. (If there are no covariates, however, heft will provide a more flexible model using cubic splines.)
penalty	the parameter to be used in the AIC criterion. The method chooses the number of knots that minimizes -2 * loglikelihood + penalty * (dimension). The default is to use penalty = log(samplesize) as in BIC. The effect of this parameter is summarized in summary.hare.
maxdim	maximum dimension (default is 6*\mbox{length(data)}^0.2).
exclude	combinations to be excluded - this should be a matrix with 2 columns - if for example exclude[1, 1] = 2 and exclude[1, 2] = 3 no interaction between covariate 2 and 3 is included. 0 represents time.
include	those combinations that can be included. Should have the same format as exclude. Only one of exclude and include can be specified .
prophaz	should the model selection be restricted to proportional hazards models?
additive	should the model selection be restricted to additive models?
linear	vector indicating for which of the variables no knots should be entered. For example, if linear = c(2, 3) no knots for either covariate 2 or 3 are entered. 0 represents time. The default is none.
fit	hare object. If fit is specified, hare adds basis functions starting with those in fit.
silent	suppresses the printing of diagnostic output about basis functions added or deleted, Rao-statistics, Wald-statistics and log-likelihoods.

Value

An object of class hare, which is organized to serve as input for plot.hare, summary.hare, dhare (conditional density), hhare (conditional hazard rate), phare (conditional probabilities), qhare (conditional quantiles), and rhare (random numbers). The object is a list with the following members:

ncov	number of covariates.
ndim	number of dimensions of the fitted model.
fcts	matrix of size ndim x 6. each row is a basis function. First element: first covariate involved (0 means time); second element: which knot (0 means: constant (time) or linear (covariate)); third element: second covariate involved (NA means: this is a function of one variable); fourth element: knot involved (if the third element is NA, of no relevance); fifth element: beta; sixth element: standard error of beta.
knots	a matrix with ncov rows. Covariate i has row i+1, time has row 1. First column: number of knots in this dimension; other columns: the knots, appended with NAs to make it a matrix.
penalty	the parameter used in the AIC criterion.
max	maximum element of survival data.
ranges	column i gives the range of the i-th covariate.
logl	matrix with two columns. The i-th element of the first column is the loglikelihood of the model of dimension i. The second column indicates whether this model was fitted during the addition stage (1) or during the deletion stage (0).
sample	sample size.

Author(s)

Charles Kooperberg [e-mail].

References

Charles Kooperberg, Charles J. Stone and Young K. Truong (1995). Hazard regression. Journal of the American Statistical Association, 90, 78-94.

Charles J. Stone, Mark Hansen, Charles Kooperberg, and Young K. Truong. The use of polynomial splines and their tensor products in extended linear modeling (with discussion) (1997). Annals of Statistics, 25, 1371–1470.

See Also

heft, plot.hare, summary.hare, dhare, hhare, phare, qhare, rhare.

Examples

fit <- hare(testhare[,1], testhare[,2], testhare[,3:8]) 

polspline documentation built on May 29, 2024, 3:38 a.m.