|Title||Semiparametric Additive Model for Estimating Risk Difference in Multicenter Studies.|
|Publication Type||Journal Article|
|Year of Publication||2018|
|Authors||Zeng, Donglin, Noorie Hyun, and Jianwen Cai|
Many cancer studies are conducted in multiple centers. While they have the advantage of more patients and larger population, center-to-center heterogeneity could be significant such that it cannot be ignored in analysis. In this paper, we propose semiparametric additive risk models with a general link function to estimate risk effects while accounting for center-specific baseline function. We propose an estimating equation for inference and show that the derived estimators are consistent and asymptotically normal. Simulation studies demonstrate good small-sample performance of the proposed method. We apply the method to analyze data from the Study of Left Ventricular Dysfunction (SOLVD) in 1990 and discuss application to one-to-one matched design.
|Alternate Journal||Biostat Epidemiol|
|Original Publication||Semiparametric additive model for estimating risk difference in multicenter studies.|
|PubMed Central ID||PMC6322696|
|Grant List||P01 CA142538 / CA / NCI NIH HHS / United States |
R01 GM124104 / GM / NIGMS NIH HHS / United States
Semiparametric Additive Model for Estimating Risk Difference in Multicenter Studies.