基于精确样本量的小健康风险评估。

Assessment of small health risks based on exact sample sizes.

作者信息

Abt K, Gülich A

机构信息

University of Frankfurt/Main, Germany, Medical School, Department of Biomathematics, Germany.

出版信息

Stat Med. 1996 Jan 30;15(2):183-95. doi: 10.1002/(SICI)1097-0258(19960130)15:2<183::AID-SIM154>3.0.CO;2-S.

DOI:10.1002/(SICI)1097-0258(19960130)15:2<183::AID-SIM154>3.0.CO;2-S

PMID:8614754

Abstract

Exact sample sizes and critical numbers of cases for the rejection of a known event probability (10(-2) to 10(-6)) in favour of an increased probability (1.5- to 50-fold) at levels -alpha;beta- = -0.05; 0.10- and -alpha;beta- = -0.10;0.05- are presented. The numbers are thoroughly validated using the characteristics of the confidence interval for the unknown true event probability. Equivalence is shown to be obtainable for the tolerated maximal value of the relative risk and the upper limit of the confidence interval for the true event probability. Also demonstrated is the use of the tables for planned actions to reduce given empirical risks. In addition, use of the tables is shown for judging results from given data sets.

摘要

给出了在显著性水平-α;β- = -0.05; 0.10-和-α;β- = -0.10;0.05-下，用于拒绝已知事件概率（10^(-2)至10^(-6)）而支持概率增加（1.5至50倍）的确切样本量和临界病例数。这些数字通过未知真实事件概率的置信区间特征进行了全面验证。结果表明，对于相对风险的容许最大值和真实事件概率的置信区间上限，可实现等效性。还展示了如何使用这些表格来规划行动以降低给定的经验风险。此外，还展示了如何使用这些表格来判断给定数据集的结果。