groupedSurv

Efficient Estimation of Grouped Survival Models Using the Exact Likelihood Function

These 'Rcpp'-based functions compute the efficient score statistics for grouped time-to-event data (Prentice and Gloeckler, 1978), with the optional inclusion of baseline covariates. Functions for estimating the parameter of interest and nuisance parameters, including baseline hazards, using maximum likelihood are also provided. A parallel set of functions allow for the incorporation of family structure of related individuals (e.g., trios). Note that the current implementation of the frailty model (Ripatti and Palmgren, 2000) is sensitive to departures from model assumptions, and should be considered experimental. For these data, the exact proportional-hazards-model-based likelihood is computed by evaluating multiple variable integration. The integration is accomplished using the 'Cuba' library (Hahn, 2005), and the source files are included in this package. The maximization process is carried out using Brent's algorithm, with the C++ code file from John Burkardt and John Denker (Brent, 2002).

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Package
groupedSurv
Type
Package
Title
Efficient Estimation of Grouped Survival Models Using the Exact Likelihood Function
Version
1.0.1
Date
2018-05-15
Author
Jiaxing Lin [aut], Alexander Sibley [aut], Tracy Truong [aut], Kouros Owzar [aut], Zhiguo Li [aut], Yu Jiang [ctb], Janice McCarthy [ctb], Andrew Allen [ctb]
Maintainer
Jiaxing Lin
Description
These 'Rcpp'-based functions compute the efficient score statistics for grouped time-to-event data (Prentice and Gloeckler, 1978), with the optional inclusion of baseline covariates. Functions for estimating the parameter of interest and nuisance parameters, including baseline hazards, using maximum likelihood are also provided. A parallel set of functions allow for the incorporation of family structure of related individuals (e.g., trios). Note that the current implementation of the frailty model (Ripatti and Palmgren, 2000) is sensitive to departures from model assumptions, and should be considered experimental. For these data, the exact proportional-hazards-model-based likelihood is computed by evaluating multiple variable integration. The integration is accomplished using the 'Cuba' library (Hahn, 2005), and the source files are included in this package. The maximization process is carried out using Brent's algorithm, with the C++ code file from John Burkardt and John Denker (Brent, 2002).
License
GPL (>= 2)
Imports
Rcpp (>= 0.12.4), doParallel, doRNG, parallel, foreach, qvalue
LinkingTo
Rcpp, RcppEigen, BH
Suggests
knitr, snplist, GenABEL
VignetteBuilder
knitr
BuildVignettes
yes
NeedsCompilation
yes
RoxygenNote
6.0.1
Packaged
2018-05-15 20:14:07 UTC; jl354
Repository
CRAN
Date/Publication
2018-05-15 21:42:23 UTC

install.packages('groupedSurv')

1.0.1

4 days ago

Jiaxing Lin

GPL (>= 2)

Imports

Rcpp (>= 0.12.4), doParallel, doRNG, parallel, foreach, qvalue

Suggests

knitr, snplist, GenABEL

Discussions