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基于参数估计方法准确性的变异系数样本量规划。

Sample size planning for the coefficient of variation from the accuracy in parameter estimation approach.

作者信息

Kelley Ken

机构信息

Inquiry Methodology Program, Indiana University, Bloomington, Indiana 47405, USA.

出版信息

Behav Res Methods. 2007 Nov;39(4):755-66. doi: 10.3758/bf03192966.

Abstract

The accuracy in parameter estimation approach to sample size planning is developed for the coefficient of variation, where the goal of the method is to obtain an accurate parameter estimate by achieving a sufficiently narrow confidence interval. The first method allows researchers to plan sample size so that the expected width of the confidence interval for the population coefficient of variation is sufficiently narrow. A modification allows a desired degree of assurance to be incorporated into the method, so that the obtained confidence interval will be sufficiently narrow with some specified probability (e.g., 85% assurance that the 95 confidence interval width will be no wider than to units). Tables of necessary sample size are provided for a variety of scenarios that may help researchers planning a study where the coefficient of variation is of interest plan an appropriate sample size in order to have a sufficiently narrow confidence interval, optionally with somespecified assurance of the confidence interval being sufficiently narrow. Freely available computer routines have been developed that allow researchers to easily implement all of the methods discussed in the article.

摘要

针对变异系数开发了样本量规划的参数估计方法的准确性,该方法的目标是通过实现足够窄的置信区间来获得准确的参数估计。第一种方法允许研究人员规划样本量,以使总体变异系数置信区间的预期宽度足够窄。一种改进方法允许将所需的保证程度纳入该方法,以便获得的置信区间将以某个指定概率足够窄(例如,有85%的保证,即95%置信区间宽度不超过某个单位)。针对各种可能帮助研究人员规划研究的场景提供了所需样本量的表格,在这些研究中变异系数是研究对象,以便规划合适的样本量,从而有足够窄的置信区间,还可选择具有置信区间足够窄的某种指定保证。已经开发了免费的计算机程序,使研究人员能够轻松实现本文讨论的所有方法。

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