Semiparametric additive model for estimating risk difference in multicenter studies

ABSTRACT

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.

KEYWORDS:

• Additive risk models
• estimating equation
• multi-center study
• one-to-one matched design
• proportional hazards model
• recurrent event

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Donglin Zeng

Donglin Zeng is a professor at the Department of Biostatistics in the University of North Carolina at Chapel Hill.

Noorie Hyun

Noorie Hyun is an assistant professor at the Division of Biostatistics, Institute for Health and Society, at Medical College of Wisconsin.

Jianwen Cai

Jianwen Cai is a professor at the Department of Biostatistics in the University of North Carolina at Chapel Hill.