假设检验时样本含量估计中容许误差δ 的合理选取
How to Determine Permissible Error δ Value Properly when Computing Sample Sizes in Hypothesis Tests
未经授权,不得转载,摘编本刊文章,不得使用本刊的版式设计。
申明:本刊刊出的所有文章不代表本刊主办单位和编委会的观点。
-
摘要: 目的 在假设检验样本含量的估计中,研究者无法得到总体参数间的差值时,可以有三种确定容许误差δ的做法。不同已知条件下哪一种做法适合,本文将通过实例讨论给出建议。 方法 以单样本均数检验为例,根据有无专业意义上公认的容许误差,分两大类情况讨论,阐明在实际中δ该如何取值,估算出用于最终正式实验的样本量。 结果 当存在专业意义上公认的容许误差时,同时通过预实验可以得到δ预,需先比较δ预与δ专的大小再计算所需的样本量;当不存在专业意义上公认的容许误差时,可以给定δ的一个取值范围(0.25S,0.50S)来计算样本量。以上可推广到成组设计均数比较、频率比较假设检验等凡是需要设定容许误差以实现样本含量估计的情形。 结论 假设检验时样本含量估计中容许误差δ值的选取需根据具体情形而定,可参考文中提供的流程图。Abstract: Objective There are three ways to determine permissible error δ value when researchers cannot get the difference δ between population parameters in computing sample sizes of hypothesis tests. Methods Take one-sample t-test for example and discuss how to determine δ value properly to compute the final sample size on two sides when there exists professional difference δ or not. Results Compare δ from pilot experiment and professional difference δ when professional difference δ does exist and then compute sample size; when there is no professional difference δ, we set the interval(0.25S,0.50S) to compute sample size; the results can also be applied in situations which involve permissible error like two independent sample t-test and χ2 test. Conclusion It is necessary to select δ value reasonably in different situations when computing sample sizes; a flow chart for reference in practice is provided.
下载: