| GSSE-package {GSSE} | R Documentation |
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 <liangbsunc@gmail.com>, Yuanjia Wang <yw2016@cumc.columbia.edu> and Donglin Zeng <dzeng@email.unc.edu>
Maintainer: Baosheng Liang <liangbsunc@gmail.com>
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.