aeexfit: Fits semiparametric regression models robust to informative...
In github-js/acc: Exploring Accelerometer Data

aeexfit

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)

github-js/acc documentation built on Aug. 21, 2023, 5:40 p.m.