RTI International, NC, USA.
Psychol Methods. 2009 Dec;14(4):400-12. doi: 10.1037/a0016618.
Scale score measures are ubiquitous in the psychological literature and can be used as both dependent and independent variables in data analysis. Poor reliability of scale score measures leads to inflated standard errors and/or biased estimates, particularly in multivariate analysis. Reliability estimation is usually an integral step to assess data quality in the analysis of scale score data. Cronbach's alpha is a widely used indicator of reliability but, due to its rather strong assumptions, can be a poor estimator (L. J. Cronbach, 1951). For longitudinal data, an alternative approach is the simplex method; however, it too requires assumptions that may not hold in practice. One effective approach is an alternative estimator of reliability that relaxes the assumptions of both Cronbach's alpha and the simplex estimator and thus generalizes both estimators. Using data from a large-scale panel survey, the benefits of the statistical properties of this estimator are investigated, and its use is illustrated and compared with the more traditional estimators of reliability.
量表分数在心理学文献中无处不在，可在数据分析中用作因变量和自变量。量表分数测量的可靠性差会导致标准误差膨胀和/或估计值有偏，尤其是在多元分析中。在分析量表分数数据时，可靠性估计通常是评估数据质量的一个重要步骤。克朗巴赫α是一种广泛使用的可靠性指标，但由于其假设较强，因此可能是一个较差的估计量（L. J. Cronbach，1951）。对于纵向数据，另一种方法是单因素法；然而，它也需要在实践中可能不成立的假设。一种有效的方法是一种可靠性的替代估计量，它放宽了克朗巴赫α和单因素估计量的假设，从而推广了这两种估计量。利用一项大规模面板调查的数据，研究了该估计量的统计性质的优势，并说明了其使用方法，并与更传统的可靠性估计量进行了比较。
