A comparison of bifactor and second-order models of quality of life
A comparison of bifactor and second-order models of quality of life
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DOI：
10.1207/s15327906mbr4102_5
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发表时间：
2006-01-01
影响因子：
3.8
通讯作者：
Sousa, Karen H.
中科院分区：
文献类型：
--
作者：
Chen, Fang Fang;West, Stephen G.;Sousa, Karen H.
双因子和二阶因子模型是两种替代方法，用于表示由几个高度相关的域组成的一般结构。使用生活质量数据集（N = 403）比较双因素和二阶模型。双因素模型确定了三个，而不是假设的四个，领域的具体因素超出了一般因素。双因子模型对数据的拟合明显优于二阶模型。双因素模型允许更容易地解释特定领域的因素和外部变量之间的关系，超过一般因素。与文献相反，在给定合理样本量的情况下，在一个实际和一个模拟示例中，存在足够的功效来区分双因子模型和相应的二阶模型。讨论了双因子模型优于二阶模型的优点。
Bifactor and second-order factor models are two alternative approaches for representing general constructs comprised of several highly related domains. Bifactor and second-order models were compared using a quality of life data set (N = 403). The bifactor model identified three, rather than the hypothesized four, domain specific factors beyond the general factor. The bifactor model fit the data significantly better than the second-order model. The bifactor model allowed for easier interpretation of the relationship between the domain specific factors and external variables, over and above the general factor. Contrary to the literature, sufficient power existed to distinguish between bifactor and corresponding second-order models in one actual and one simulated example, given reasonable sample sizes. Advantages of bifactor models over second-order models are discussed.