Sherman C D, Portier C J
Laboratory of Quantitative and Computational Biology, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina 27709, USA.
Math Biosci. 1996 May;134(1):35-50. doi: 10.1016/0025-5564(95)00105-0.
Stochastic mathematical models of carcinogenesis have been used to quantify cancer risks for about 40 years. As more detailed data of the cancer process are obtained, mathematical models try to incorporate this information and as a result become more complex and sometimes analytically and numerically intractable. Simulation studies have become an important tool for examining the operating characteristics of the models of interest. The many quantities one can examine using this tool include bias in parameter estimates, adequacy of approximation methods, and the appropriateness of large sample generalizations to small studies. This manuscript describes a general method of stochastic simulation that may be carried out for arbitrarily complicated stochastic models of carcinogenesis.
癌症发生的随机数学模型已被用于量化癌症风险约40年了。随着获得关于癌症过程的更详细数据，数学模型试图纳入这些信息，结果变得更加复杂，有时在分析和数值计算上难以处理。模拟研究已成为检验相关模型运行特征的重要工具。使用该工具可以检验的众多量包括参数估计中的偏差、近似方法的充分性以及大样本推广对小研究的适用性。本文描述了一种随机模拟的通用方法，可针对任意复杂的癌症发生随机模型进行。
