Department of Statistics, Iowa State University, Ames, IA 50011, USA.
Psychol Methods. 2010 Dec;15(4):368-85. doi: 10.1037/a0020142.
The conventional fixed-effects (FE) and random-effects (RE) confidence intervals that are used to assess the average alpha reliability across multiple studies have serious limitations. The FE method, which is based on a constant coefficient model, assumes equal reliability coefficients across studies and breaks down under minor violations of this assumption. The RE method, which is based on a random coefficient model, assumes that the selected studies are a random sample from a normally distributed superpopulation. The RE method performs poorly in typical meta-analytic applications where the studies have not been randomly sampled from a normally distributed superpopulation or have been randomly sampled from a nonnormal superpopulation. A new confidence interval for the average reliability coefficient of a specific measurement scale is based on a varying coefficient statistical model and is shown to perform well under realistic conditions of reliability heterogeneity and nonrandom sampling of studies. New methods are proposed for assessing reliability moderator effects. The proposed methods are especially useful in meta-analyses that involve a small number of carefully selected studies for the purpose of obtaining a more accurate reliability estimate or to detect factors that moderate the reliability of a scale.
传统的固定效应（FE）和随机效应（RE）置信区间被用于评估多个研究中平均α可靠性，但其存在严重的局限性。FE 方法基于恒定系数模型，假设各研究的可靠性系数相同，但在该假设受到轻微违反时就会失效。RE 方法基于随机系数模型，假设所选研究是正态分布超总体的随机样本。在典型的元分析应用中，RE 方法表现不佳，这些研究并非是从正态分布超总体中随机抽取的，或者是从非正态超总体中随机抽取的。一种新的特定测量量表平均可靠性系数的置信区间基于变系数统计模型，在可靠性异质性和研究非随机抽样的实际条件下表现良好。还提出了用于评估可靠性调节效应的新方法。所提出的方法在元分析中特别有用，这些元分析涉及少量精心选择的研究，目的是获得更准确的可靠性估计，或检测调节量表可靠性的因素。
