|Title||lclGWAS: Efficient estimation of discrete-time multivariate frailty model using exact likelihood function for grouped survival data (R).|
|Year of Publication||2016|
|Authors||Lin, Jiaxing, Alexander Sibley, Trach Truong, Nancy Cox, Eileen Dolan, Yu Jiang, Janice M. McCarthy, Andrew S. Allen, Kouros Owzar, and Zhiguo Li|
THIS PACKAGE IS SUPERSEDED BY package groupedSURV
The core of this 'Rcpp' based package is several functions to estimate the baseline hazard, frailty variance, and fixed effect parameter for a discrete-time shared frailty model with random effects. The functions are designed to analyze grouped time-to-event data accounting for family structure of related individuals (i.e., trios). The core functions include two processes: (1) evaluate the multivariable integration to compute the exact proportional hazards model based likelihood and (2) estimate the desired parameters using maximum likelihood estimation. The integration is evaluated by the 'Cuhre' algorithm from the 'Cuba' library (Hahn, T., Cuba-a library for multidimensional numerical integration, Comput. Phys. Commun. 168, 2005, 78-95 ), and the source files of the 'Cuhre' function 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, R.,Algorithms for Minimization without Derivatives, Dover, 2002, ISBN 0-486-41998-3).
|Original Publication||lclGWAS: Efficient estimation of discrete-time multivariate frailty model using exact likelihood function for grouped survival data (R).|