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当样本的数量是空白数量的整数倍时,置信区间会得到改善。

Improved confidence intervals when the sample is counted an integer times longer than the blank.

机构信息

University of Colorado Hospital, Aurora, CO 80045, USA.

出版信息

Health Phys. 2011 May;100 Suppl 2:S67-70. doi: 10.1097/HP.0b013e31820448c4.

Abstract

Past computer solutions for confidence intervals in paired counting are extended to the case where the ratio of the sample count time to the blank count time is taken to be an integer, IRR. Previously, confidence intervals have been named Neyman-Pearson confidence intervals; more correctly they should have been named Neyman confidence intervals or simply confidence intervals. The technique utilized mimics a technique used by Pearson and Hartley to tabulate confidence intervals for the expected value of the discrete Poisson and Binomial distributions. The blank count and the contribution of the sample to the gross count are assumed to be Poisson distributed. The expected value of the blank count, in the sample count time, is assumed known. The net count, OC, is taken to be the gross count minus the product of IRR with the blank count. The probability density function (PDF) for the net count can be determined in a straightforward manner.

摘要

过去用于配对计数置信区间的计算机解决方案已扩展到样本计数时间与空白计数时间的比值被视为整数 IRR 的情况。以前,置信区间被命名为 Neyman-Pearson 置信区间;更准确地说,它们应该被命名为 Neyman 置信区间或简单地称为置信区间。所使用的技术模仿了 Pearson 和 Hartley 用于为离散泊松和二项式分布的期望值制表置信区间的技术。空白计数和样本对总计数的贡献被假定为泊松分布。在样本计数时间内,空白计数的期望值被假定为已知。净计数 OC 被视为总计数减去 IRR 与空白计数的乘积。净计数的概率密度函数 (PDF) 可以以直接的方式确定。

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