Setodji Claude Messan, Lockwood J R, McCaffrey Daniel F, Elliott Marc N, Adams John L
Rand Health Q. 2012 Mar 1;2(1):18. eCollection 2012 Spring.
The Modified Kalman Filter approach for pooling information across time and across outcomes is shown to improve accuracy in national estimates of health outcomes, including cancer, diabetes, and hypertension, especially in small racial/ethnic subgroups. The developed SAS macro models true health states in each subgroup assuming a linear time evolution and an autoregressive deviation around such trend. The macro provides multiple options for users.
用于跨时间和跨结果汇总信息的修正卡尔曼滤波方法被证明可提高国家健康结果估计的准确性，这些结果包括癌症、糖尿病和高血压，尤其是在小种族/族裔亚组中。所开发的SAS宏在假设线性时间演变以及围绕该趋势的自回归偏差的情况下，对每个亚组中的真实健康状态进行建模。该宏为用户提供了多种选项。
