Abstract
We propose a simple approach predicting the cumulative risk of disease accommodating predictors with time-varying effects and outcomes subject to censoring. We use a nonparametric function for the coefficient of the time-varying effect and handle censoring through self-consistency equations that redistribute the probability mass of censored outcomes to the right. The computational procedure is extremely convenient and can be implemented by standard software. We prove large sample properties of the proposed estimator and evaluate its finite sample performance through simulation studies. We apply the method to estimate the cumulative risk of developing Huntington's disease (HD) from subjects with huntingtin gene mutation using a large collaborative HD study data and illustrate an inverse relationship between the cumulative risk of HD and the length of cytosine-adenine-guanine repeats in the huntingtin gene.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 2427-2443 |
| Number of pages | 17 |
| Journal | Statistics in Medicine |
| Volume | 34 |
| Issue number | 16 |
| DOIs | |
| State | Published - Jul 20 2015 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Epidemiology
- Statistics and Probability
Cite this
}
Predicting cumulative risk of disease onset by redistributing weights. / Chen, Tianle; Ma, Yanyuan; Wang, Yuanjia.
In: Statistics in Medicine, Vol. 34, No. 16, 20.07.2015, p. 2427-2443.Research output: Contribution to journal › Article
TY - JOUR
T1 - Predicting cumulative risk of disease onset by redistributing weights
AU - Chen, Tianle
AU - Ma, Yanyuan
AU - Wang, Yuanjia
PY - 2015/7/20
Y1 - 2015/7/20
N2 - We propose a simple approach predicting the cumulative risk of disease accommodating predictors with time-varying effects and outcomes subject to censoring. We use a nonparametric function for the coefficient of the time-varying effect and handle censoring through self-consistency equations that redistribute the probability mass of censored outcomes to the right. The computational procedure is extremely convenient and can be implemented by standard software. We prove large sample properties of the proposed estimator and evaluate its finite sample performance through simulation studies. We apply the method to estimate the cumulative risk of developing Huntington's disease (HD) from subjects with huntingtin gene mutation using a large collaborative HD study data and illustrate an inverse relationship between the cumulative risk of HD and the length of cytosine-adenine-guanine repeats in the huntingtin gene.
AB - We propose a simple approach predicting the cumulative risk of disease accommodating predictors with time-varying effects and outcomes subject to censoring. We use a nonparametric function for the coefficient of the time-varying effect and handle censoring through self-consistency equations that redistribute the probability mass of censored outcomes to the right. The computational procedure is extremely convenient and can be implemented by standard software. We prove large sample properties of the proposed estimator and evaluate its finite sample performance through simulation studies. We apply the method to estimate the cumulative risk of developing Huntington's disease (HD) from subjects with huntingtin gene mutation using a large collaborative HD study data and illustrate an inverse relationship between the cumulative risk of HD and the length of cytosine-adenine-guanine repeats in the huntingtin gene.
UR - http://www.scopus.com/inward/record.url?scp=84930415542&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84930415542&partnerID=8YFLogxK
U2 - 10.1002/sim.6499
DO - 10.1002/sim.6499
M3 - Article
C2 - 25847392
AN - SCOPUS:84930415542
VL - 34
SP - 2427
EP - 2443
JO - Statistics in Medicine
JF - Statistics in Medicine
SN - 0277-6715
IS - 16
ER -