GSSE-package: Genotype-Specific Survival Estimation

In GSSE: Genotype-Specific Survival Estimation

Description

The package ‘GSSE’ (Genotype-Specific Survival Estimation) is made to implement a fully efficient sieve maximum likelihood method to estimate genotype-specific distribution of time-to-event outcomes under a nonparametric model. The package can handle missing genotypes in pedigrees. We estimate time-dependent hazard ratio between two genetic mutation groups using B-splines and apply nonparametric maximum likelihood estimation to the reference baseline hazard function. The estimators are calculated via an expectation-maximization algorithm.

Details

Package:	GSSE
Type:	Package
Version:	0.1
Date:	2015-10-17
License:	GPL (>= 2)

The main function is Sieve_NPMLE_Switch(). See the documentation file with examples.

Author(s)

Baosheng Liang <[e-mail]>, Yuanjia Wang <[e-mail]> and Donglin Zeng <[e-mail]>

Maintainer: Baosheng Liang <[e-mail]>

References

Wang, Y., Clark, L. N., Louis, E. D., Mejia-Santana, H., Harris, J., Cote, L. J., ... & Marder, K. (2008). Risk of Parkinson disease in carriers of parkin mutations: estimation using the kin-cohort method. Archives of neurology, 65(4), 467-474.

Qin, J., Garcia, T., Ma, Y., Tang, M., Marder, K. & Wang, Y. (2014). Combining isotonic regression and EM algorithm to predict genetic risk under monotonicity constraint. The Annals of Applied Statistics 8(2), 1182-1208.

Wang, Y., Liang, B., Tong, X., Marder, K., Bressman, S., Orr-Urtreger, A., Giladi, N. & Zeng, D. (2015). Efficient estimation of nonparametric genetic risk function with censored data. Biometrika, 102(3), 515-532.

GSSE documentation built on May 2, 2019, 12:40 p.m.