Zhang Peng, Liu Juxin, Dong Jianghu, Holovati Jelena L, Letcher Brenda, McGann Locksley E
Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, Canada.
Biometrics. 2012 Mar;68(1):268-74. doi: 10.1111/j.1541-0420.2011.01641.x. Epub 2011 Jun 20.
We develop a Bayesian approach to a calibration problem with one interested covariate subject to multiplicative measurement errors. Our work is motivated by a stem cell study with the objective of establishing the recommended minimum doses for stem cell engraftment after a blood transplant. When determining a safe stem cell dose based on the prefreeze samples, the postcryopreservation recovery rate enters in the model as a multiplicative measurement error term, as shown in the model. We examine the impact of ignoring measurement errors in terms of asymptotic bias in the regression coefficient. According to the general structure of data available in practice, we propose a two-stage Bayesian method to perform model estimation via R2WinBUGS (Sturtz, Ligges, and Gelman, 2005, Journal of Statistical Software 12, 1-16). We illustrate this method by the aforementioned motivating example. The results of this study allow routine peripheral blood stem cell processing laboratories to establish recommended minimum stem cell doses for transplant and develop a systematic approach for further deciding whether the postthaw analysis is warranted.
我们针对一个校准问题开发了一种贝叶斯方法，该问题涉及一个受乘法测量误差影响的感兴趣协变量。我们的工作受到一项干细胞研究的推动，其目的是确定血液移植后干细胞植入的推荐最小剂量。在根据冷冻前样本确定安全的干细胞剂量时，如模型所示，冷冻保存后的回收率作为乘法测量误差项进入模型。我们从回归系数的渐近偏差角度研究了忽略测量误差的影响。根据实际中可用数据的一般结构，我们提出了一种两阶段贝叶斯方法，通过R2WinBUGS软件（Sturtz、Ligges和Gelman，2005年，《统计软件杂志》12卷，第1 - 16页）进行模型估计。我们通过上述激励示例来说明这种方法。本研究结果使常规外周血干细胞处理实验室能够确定移植的推荐最小干细胞剂量，并开发一种系统方法来进一步决定是否有必要进行解冻后分析。
