ADAPTATION OF NEW STATISTICAL IDEAS FOR MEDICINE

从广泛的角度将有用的统计学思想引入生物医学实践 来源范围，包括理论研究和发展 其他应用领域。这笔赠款的长期目的是 加快将前景看好的新统计技术转移到健康领域- 相关应用程序。这里提出了五个具体目标，所有这些目标 它涉及计算机密集型方法和新的 统计理论的发展。自助法和排列法 对一些特定的生物医学问题提出了建议：在分析 医学图像的精度测量，以及染色体的精度测量 通过辐射混合动力车订购。更一般的类型问题 在生物统计工作中遇到的情况也在调查中：背景 准确的可信区间，评估离散化的准确性 估计，如系统发育树，并利用贝叶斯思想 以客观的方式。调查从以下几个方面展开 几个有利位置，斯坦福大学统计部门，医疗 学校和人类基因组计划。

Useful statistical ideas are drawn into biomedical practice from a wide range of sources, including theoretical research and developments in other application areas. The long-term purpose of this grant is to speed the transfer of promising new statistical technology into health- related applications. Five specific aims are proposed here, all of which involve a combination of computer-intensive methodology with new developments in statistical theory. Bootstrap and permutation methods are suggested for some specific biomedical problems: in the analysis of accuracy measurements for medical images, and also for chromosomal ordering via radiation hybrids. More general problems of the types encountered in biostatistical work are also under investigation: setting accurate confidence intervals, assessing the accuracy of discrete estimates such as phylogenetic trees, and making use of Bayesian ideas in an objective manner. The investigation pursues these topics from several vantage points, the Stanford statistics department, the medical school, and the Human Genome project.