摘要
目的通过混合样本方法减小检测精度带来的误差,提高对低总体率估计的精度。方法通过公式推导说明对给定的灵敏度和特异度,有其适宜检测的理想总体率值;在给定总体率、灵敏度和特异度下,利用计算机模拟和计算不同混合样本大小下对率估计的平均相对误差。结果当实际总体率小于理想值时,通过样本混合可以调整率值,从而减小检测精度带来的误差。结论在低总体率下,针对给定的灵敏度、特异度,混合样本方法可以极大地提高率的估计精度,且减少检测的次数。
Objective To use the pooled sampling method to reduce the error caused by the detecting precision,so as to improve the accuracy of population rate estimates.Methods A formula was deduced on how to obtain the ideal rate under given sensitivity and specificity,and the mean relative errors of rate estimation with different pool sizes were simulated and calculated using software SAS 9.1.Results When the actual rate was lower than the ideal rate,the errors caused by the detecting precision could be greatly reduced through adjusting the rate of mixed samples.Conclusion When the population rate is low,the accuracy of rate estimation can be improved and the numbers of tests can be reduced by using pooled sampling method under given specificity and sensitivity.
出处
《第二军医大学学报》
CAS
CSCD
北大核心
2011年第1期72-75,共4页
Academic Journal of Second Military Medical University
关键词
二项分布
总体率
混合样本
灵敏度
特异度
binomial distribution
population rate
pooled sample
sensitivity
specificity