Reliability and Statistical Power: How Measurement Fallibility Affects Power and Required Sample Sizes for Several Parametric and Nonparametric Statistics
Reliability and Statistical Power: How Measurement Fallibility Affects Power and Required Sample Sizes for Several Parametric and Nonparametric Statistics
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DOI：
10.22237/jmasm/1177992480
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发表时间：
2007-05-01
影响因子：
--
通讯作者：
Gocmen, Gulsah
中科院分区：
文献类型：
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作者：
Kanyongo, Gibbs Y.;Brook, Gordon P.;Gocmen, Gulsah
被认为是可靠性和统计功率之间的关系，并表，占可靠性降低。通过一系列Monte Carlo实验来确定信度变化对参数和非参数统计方法的影响，包括配对样本依赖t检验、合并方差独立t检验、三水平单因素方差分析、配对样本的Wilcoxon符号秩检验和独立组的Mann-Whitney-Wilcoxon检验。创建功效表，说明给定样本量的可靠性降低导致统计功效降低。创建了样本量表，以提供实现基于多个可靠性水平的给定统计功效水平所需的近似样本量。
The relationship between reliability and statistical power is considered, and tables that account for reduced reliability are presented. A series of Monte Carlo experiments were conducted to determine the effect of changes in reliability on parametric and nonparametric statistical methods, including the paired samples dependent t test, pooled-variance independent t test, one-way analysis of variance with three levels, Wilcoxon signed-rank test for paired samples, and Mann-Whitney-Wilcoxon test for independent groups. Power tables were created that illustrate the reduction in statistical power from decreased reliability for given sample sizes. Sample size tables were created to provide the approximate sample sizes required to achieve given levels of statistical power based for several levels of reliability.