| aeexfit {acc} | R Documentation |
Fits semiparametric regression models robust to informative observation times and censoring
Description
Fits semiparametric regression models robust to informative observation times and censoring
Usage
aeexfit(formula, data, weight, se, control=list(), boot)
Arguments
formula |
A formula object as returned by aee. |
data |
A data frame which includes individuals' ID, observation times, and minutes of physical activity since the last observation time. |
weight |
A vector of sampling weights, for each individual.By default, no sampling weights are applied. |
se |
The method of estimating standard errors can be chosen by the argument se. Two options are available: i) the sandwhich estimation (se = 'Sandwich'), or ii) the bootstrap procedure (se = 'Bootstrap'). |
control |
A list of control parameters. See 'Details'. |
boot |
The number of resamples generated for the bootstrap procedure. |
Details
The control argument is a list athat can supply any of the following components:
betaInit: Initial value for covariate coefficient, default is 0.
interval: Initial search interval for solving beta. Default is (-5,5).
maxIter: Maximum iterations allowed. Default is 150.
absTol: Absolute tolerance. Default is 1e-6.
relTol: Relative tolerance. Default is 1e-6.
a: A tune parameter. Default is .1. In case of gamma fraility, "a" corresponds to the value of both shape and rate parameters.
Author(s)
Jaejoon Song <jjsong2@mdanderson.org>
References
Wang, X. and Yan, J. (2011). Fitting semiparametric regressions for panel count survival data with an R package spef. Computer Methods and Programs in Biomedicine, 104, 278-285.
Wang, X., Ma, S., and Yan, J. (2013). Augmented estimating equations for semiparametric panel count regression with informative observation times and censoring time. Statistica Sinica, 23, 359-381.
Examples
## Not run:
data(NHANES)
formula <- aee(ID, Day, mvpaMinutes) ~ VO2max
# Standard errors are obtained using sandwich estimation
fitted <- aeexfit(formula = formula, data = NHANES, se = "Sandwich")
summary(fitted)
## End(Not run)