中文摘要：

在心理、教育和管理等研究领域中，经常会碰到两水平（两层）的数据结构，如学生嵌套在班级中，员工嵌套在企业中。在两水平研究中，被试通常不是独立的，如果直接用单水平信度公式进行估计，会高估测验信度。文献上已有研究讨论如何更准确地估计两水平研究中单维测验的信度。本研究指出了现有的估计公式的不足之处，用两水平验证性因子分析推导出一个新的信度公式，举例演示如何计算，并给出简单的计算程序。

英文摘要：

In the studies of psychology, education and management, we often face data with a two-level structure. For example, students are nested within schools, and employees are nested within enterprises. In such two-level studies, subjects （e. g. , students, employees） do not perform independently. Subjects within the same group are usually correlated with each other. The independence assumption on individuals in such two-level studies is usually not true. Estimating test reliability is an important step in data analysis. If test reliability is overestimated, the statistical results based on the test are misleading. Reliability is not an intrinsic property of a test; rather, it varies depending on the population in which it is used. Previous research showed that test reliability would be overestimated if the nested relationship was not considered. Hence, test reliability estimation methods that are proposed under the frame of single-level designs are not appropriate for the two-level designs. Raykov and du Toit （2005） deduced a formula for estimating reliability of unidimensional test in the two-level designs based on a two-level confirmatory factor analysis model in which factor loadings of the between-group part were constrained to be equal to their counterparts of the withingroup part. Their formula is only suitable for a rather special situation when the above-referenced constraints are correct for the model. Moreover, their method is difficult to understand, and their program is too complicated to be imitated. Till now, most empirical researchers still estimate test reliability as in a single-level design even if the study is a two-level design. So it is necessary- to study how to estimate reliability in two-level design and propose a simpler program for computation. We deduced a new formula to estimate the test reliability of the unidimensional test in two-level designs based on a two-level confirmatory factor analysis. Whether factor loadings of the between-group part are fixed or not, the tormula is app