| 来源类型 | Article |
| 规范类型 | 其他 |
| DOI | 10.1016/0270-0255(86)90085-0 |
| Evaluating the effects of observed and unobserved diffusion processes in survival analysis of longitudinal data. | |
| Yashin AI; Manton KG; Stallard E | |
| 发表日期 | 1986 |
| 出处 | Mathematical Modelling 7 (9-12): 1353-1363 |
| 出版年 | 1986 |
| 语种 | 英语 |
| 摘要 | In biostatistical, epidemiological and demographic studies of human survival it is often necessary to consider the dynamics of physiological processes and their influences on observed mortality rates. The parameters of a stochastic covariate process can be estimated using a conditional Gaussian strategy based on the mortality model presented in M.A. Woodbury and K.G. Manton, A random walk model of human mortality and aging. Theor. Popul. Biol. 11, 37–48 (1977) and A.I. Yashin, K.G. Manton, and J.W. Vaupel, Mortality and aging in a heterogeneous population: A stochastic process model with observed and unobserved variables. Theor. Popul. Biol., in press. (1985). The utility of this approach for modeling survival in a longitudinally followed population is discussed—especially in the context of conducing coordinated analyses of multiple similarly constituted databases. Furthermore, the conditional Gaussian approach offers several substantive and computational advantages over the Cameron- Martin approach R.H. Cameron and W.T. Martin, The Wiener measure of Hilbert neighborhoods in the space of real continuous functions. |
| 主题 | World Population (POP) |
| URL | http://pure.iiasa.ac.at/id/eprint/12542/ |
| 来源智库 | International Institute for Applied Systems Analysis (Austria) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/126941 |
| 推荐引用方式 GB/T 7714 | Yashin AI,Manton KG,Stallard E. Evaluating the effects of observed and unobserved diffusion processes in survival analysis of longitudinal data.. 1986. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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